Theory of Computing Report

Authors: Yumou Fei, Dor Minzer, Shuo Wang

We prove that for all $\varepsilon>0$, there exists a positive integer $k$ such that given a $4$-to-$1$ game $Ψ$ with alphabet size at most $k$, it is $\mathbf{NP}$-hard to distinguish between the case that $\mathrm{val}(Ψ)=1$ and the case that $\mathrm{val}(Ψ)\leq \varepsilon$. This confirms the $4$-to-$1$ Games Conjecture from [Khot, \textit{CCC 2002}]. Previously, the best known result, due to [Dinur, Khot, Kindler, Minzer, Safra], established the almost-perfect completeness version (but applied to the stricter problem of $2$-to-$1$ games). Using results from the literature, we get the following implications: (1) for all $k\in \mathbb{N}$, given a $3$-colorable graph $G$, it is $\mathbf{NP}$-hard to find a proper $k$-coloring; (2) for all $δ>0$, given a $2$-colorable $3$-uniform hypergraph $G$, it is $\mathbf{NP}$-hard to find in it an independent set containing at least $δ$ fraction of the vertices. Our proof is a three-step construction that builds on the two-step framework of [Dinur, Khot, Kindler, Minzer, Safra]. In the outer-PCP step, we use quadratic equations to gain perfect completeness. We then construct a new middle PCP that performs low-rank tests while preserving a key covering property. Finally, we construct a new inner PCP based on a tensor of the standard Grassmann encoding with its low-rank variant due to [Golowich, FOCS 2023].

Authors: Yumou Fei, Dor Minzer, Shuo Wang

We prove that for all $\varepsilon>0$, there exists a positive integer $k$ such that given a $4$-to-$1$ game $Ψ$ with alphabet size at most $k$, it is $\mathbf{NP}$-hard to distinguish between the case that $\mathrm{val}(Ψ)=1$ and the case that $\mathrm{val}(Ψ)\leq \varepsilon$. This confirms the $4$-to-$1$ Games Conjecture from [Khot, \textit{CCC 2002}]. Previously, the best known result, due to [Dinur, Khot, Kindler, Minzer, Safra], established the almost-perfect completeness version (but applied to the stricter problem of $2$-to-$1$ games). Using results from the literature, we get the following implications: (1) for all $k\in \mathbb{N}$, given a $3$-colorable graph $G$, it is $\mathbf{NP}$-hard to find a proper $k$-coloring; (2) for all $δ>0$, given a $2$-colorable $3$-uniform hypergraph $G$, it is $\mathbf{NP}$-hard to find in it an independent set containing at least $δ$ fraction of the vertices. Our proof is a three-step construction that builds on the two-step framework of [Dinur, Khot, Kindler, Minzer, Safra]. In the outer-PCP step, we use quadratic equations to gain perfect completeness. We then construct a new middle PCP that performs low-rank tests while preserving a key covering property. Finally, we construct a new inner PCP based on a tensor of the standard Grassmann encoding with its low-rank variant due to [Golowich, FOCS 2023].

Friday, October 09 2026, 00:00

The rank of $3\times 3$ matrix multiplication over $\mathbb{F}_2$ is 23

Authors: Tejasvi Singh Tomar

The rank of the tensor of $3\times 3$ matrix multiplication over the field with two elements is at most $23$ by Laderman's algorithm, and Rudich and Rousseau recently proved that it is at least $22$. We prove that it equals $23$. Hence Laderman's algorithm uses the fewest multiplications among all bilinear algorithms over $\mathbb{F}_2$ and among all bilinear algorithms with integer coefficients. The proof uses the substitution method in the form developed in recent work of D'Ambrosio, Wang and Yang et al.: a subspace $S$ of the space of first factors contains at most $r-R(S)$ first factors of a decomposition of length $r$, where $R(S)$ is the rank of the tensor modulo $S$. We raise the known lower bounds on $R(S)$ for $111$ of Wang's $496$ symmetry classes of subspaces. One of these bounds, $R(S)\ge 21$ for a point spanned by a matrix of rank one, forces the $22$ first factors of a decomposition of length $22$ to be distinct. A $27\times 27$ flattening of the tensor gives further constraints on the ranks of the first factors, and a separate enumeration shows that, when at least $14$ first factors have rank one, no line in a certain orbit of lines contains two first factors. A computer search then lists, up to symmetry, all sets of $22$ matrices that satisfy these constraints, and an exact completion search shows that none of them is the set of first factors of a decomposition. The computation emits certificates, which are checked in the Lean 4 proof assistant by checkers whose soundness is proved in Lean. The largest checks are evaluated as compiled code, so the proof relies on the Lean compiler in addition to its kernel.

Authors: Tejasvi Singh Tomar

The rank of the tensor of $3\times 3$ matrix multiplication over the field with two elements is at most $23$ by Laderman's algorithm, and Rudich and Rousseau recently proved that it is at least $22$. We prove that it equals $23$. Hence Laderman's algorithm uses the fewest multiplications among all bilinear algorithms over $\mathbb{F}_2$ and among all bilinear algorithms with integer coefficients. The proof uses the substitution method in the form developed in recent work of D'Ambrosio, Wang and Yang et al.: a subspace $S$ of the space of first factors contains at most $r-R(S)$ first factors of a decomposition of length $r$, where $R(S)$ is the rank of the tensor modulo $S$. We raise the known lower bounds on $R(S)$ for $111$ of Wang's $496$ symmetry classes of subspaces. One of these bounds, $R(S)\ge 21$ for a point spanned by a matrix of rank one, forces the $22$ first factors of a decomposition of length $22$ to be distinct. A $27\times 27$ flattening of the tensor gives further constraints on the ranks of the first factors, and a separate enumeration shows that, when at least $14$ first factors have rank one, no line in a certain orbit of lines contains two first factors. A computer search then lists, up to symmetry, all sets of $22$ matrices that satisfy these constraints, and an exact completion search shows that none of them is the set of first factors of a decomposition. The computation emits certificates, which are checked in the Lean 4 proof assistant by checkers whose soundness is proved in Lean. The largest checks are evaluated as compiled code, so the proof relies on the Lean compiler in addition to its kernel.

Friday, October 09 2026, 00:00

Near-Inverse-Linear Barriers for Explicit Affine Witness Isolation

Authors: Sebastian Ben Daniel

We study randomized nonuniform polynomial-size transformations that output explicit binary affine filters for circuit inputs whose nonempty satisfying sets are affine. The filter may depend on the entire input description; no affine basis is supplied. For every fixed $δ<1$, a worst-case singleton success guarantee $Ω(n^{-δ})$, where $n$ is the witness arity, implies $NP\subseteq P/poly$. More generally, any success guarantee $ω(\log n/n)$ yields satisfiability circuits of size $(s+2)^{O(1)}2^{o(v)}$ for length-$s$ descriptions with at most $v$ witness variables, hence subexponential in $v$ when $s=v^{O(1)}$. Conversely, SAT search-to-decision gives deterministic perfect isolation, making polynomial-resource fixed-exponent strong affine isolation equivalent to $NP\subseteq P/poly$. For explicit unions of at most $n^β$ affine components, success $Ω(n^{-δ})$ implies the same collapse whenever $β,δ\ge0$ and $β+δ<1$. The inverse-linear endpoint is not claimed.

Authors: Sebastian Ben Daniel

We study randomized nonuniform polynomial-size transformations that output explicit binary affine filters for circuit inputs whose nonempty satisfying sets are affine. The filter may depend on the entire input description; no affine basis is supplied. For every fixed $δ<1$, a worst-case singleton success guarantee $Ω(n^{-δ})$, where $n$ is the witness arity, implies $NP\subseteq P/poly$. More generally, any success guarantee $ω(\log n/n)$ yields satisfiability circuits of size $(s+2)^{O(1)}2^{o(v)}$ for length-$s$ descriptions with at most $v$ witness variables, hence subexponential in $v$ when $s=v^{O(1)}$. Conversely, SAT search-to-decision gives deterministic perfect isolation, making polynomial-resource fixed-exponent strong affine isolation equivalent to $NP\subseteq P/poly$. For explicit unions of at most $n^β$ affine components, success $Ω(n^{-δ})$ implies the same collapse whenever $β,δ\ge0$ and $β+δ<1$. The inverse-linear endpoint is not claimed.

Friday, October 09 2026, 00:00

Integer programming on polytopes of Chvátal rank one is as hard as lattice problems

Authors: Alberto Del Pia

A rational polyhedron has Chvátal rank at most one if a single round of Chvátal-Gomory cuts yields its integer hull. For such polyhedra, integer feasibility is in NP $\cap$ coNP by a result of Boyd and Pulleyblank from the early 1980s, so it is unlikely to be NP-hard. Whether it is polynomial has remained open since then. We answer this question negatively, under either of two standard assumptions from lattice-based cryptography. First, a polynomial-time algorithm for this problem would solve bounded distance decoding with polynomial factors in deterministic polynomial time, contradicting a widely believed conjecture. Second, assuming the hardness of learning with errors, an average-case analogue of bounded distance decoding, the problem is also hard on average, for an efficiently samplable distribution of polytopes. Both results rest on an elementary sufficient condition: a polyhedron has Chvátal rank at most one if its width is less than one along every row of some unimodular matrix. For our polytopes, such a matrix exists but is hard to find.

Authors: Alberto Del Pia

A rational polyhedron has Chvátal rank at most one if a single round of Chvátal-Gomory cuts yields its integer hull. For such polyhedra, integer feasibility is in NP $\cap$ coNP by a result of Boyd and Pulleyblank from the early 1980s, so it is unlikely to be NP-hard. Whether it is polynomial has remained open since then. We answer this question negatively, under either of two standard assumptions from lattice-based cryptography. First, a polynomial-time algorithm for this problem would solve bounded distance decoding with polynomial factors in deterministic polynomial time, contradicting a widely believed conjecture. Second, assuming the hardness of learning with errors, an average-case analogue of bounded distance decoding, the problem is also hard on average, for an efficiently samplable distribution of polytopes. Both results rest on an elementary sufficient condition: a polyhedron has Chvátal rank at most one if its width is less than one along every row of some unimodular matrix. For our polytopes, such a matrix exists but is hard to find.

Friday, October 09 2026, 00:00

Tiling 3D by Translates of a Single Polycube is Undecidable

Authors: Erik D. Demaine, Stefan Langerman

We prove co-RE-completeness, and thus undecidability, of the following problem: given a single (connected) polycube, decide whether it tiles 3D Euclidean space by translations. We reduce from Wang tiling using the decorated two-prime Sudoku construction of Greenfeld and Tao and a cyclic encoding adapted from OpenAI's 3D aperiodic tile, and apply a reduction of Kim to make the prototile connected (via faces). Dimension three is optimal: translational monotiling is known to be decidable in $\mathbb{Z}^2$ and for a single (possibly disconnected) polyomino in $\mathbb{R}^2$.

Authors: Erik D. Demaine, Stefan Langerman

We prove co-RE-completeness, and thus undecidability, of the following problem: given a single (connected) polycube, decide whether it tiles 3D Euclidean space by translations. We reduce from Wang tiling using the decorated two-prime Sudoku construction of Greenfeld and Tao and a cyclic encoding adapted from OpenAI's 3D aperiodic tile, and apply a reduction of Kim to make the prototile connected (via faces). Dimension three is optimal: translational monotiling is known to be decidable in $\mathbb{Z}^2$ and for a single (possibly disconnected) polyomino in $\mathbb{R}^2$.

Friday, October 09 2026, 00:00

A QPTAS for Stochastic Scheduling of Bernoulli Jobs

Authors: Junho Hwang

We study the classical problem of scheduling jobs with random processing times on $m$ identical machines to minimize the expected sum of completion times, for Bernoulli jobs: job $j$ takes time $p_j$ with probability $q_j$ and time $0$ otherwise, and its outcome is revealed when it starts. The benchmark is an optimal adaptive policy. We give a quasi-polynomial-time approximation scheme for every number of machines. Previously, quasi-polynomial time was known to give an $O(\log N)$-approximation, and approximation schemes were known only for a constant number of distinct sizes. The scheme rests on a simple observation: it suffices to round the times at which machines become free, rather than the times at which jobs start, to a grid whose width is proportional to the job size, and an optimal policy stretched by a factor close to one already respects such grids. We also show that every policy that fixes the order of the jobs in advance loses a factor $Ω(\log N)$, already on two machines, so a constant factor requires adapting the order to the observed outcomes. Further results include a polynomial-time adaptive rule with ratio $\min\{m,1+\sum_j q_j\}$, a simpler approximation scheme for a constant number of sizes, and #P-hardness of computing the optimal expected cost on two machines.

Authors: Junho Hwang

We study the classical problem of scheduling jobs with random processing times on $m$ identical machines to minimize the expected sum of completion times, for Bernoulli jobs: job $j$ takes time $p_j$ with probability $q_j$ and time $0$ otherwise, and its outcome is revealed when it starts. The benchmark is an optimal adaptive policy. We give a quasi-polynomial-time approximation scheme for every number of machines. Previously, quasi-polynomial time was known to give an $O(\log N)$-approximation, and approximation schemes were known only for a constant number of distinct sizes. The scheme rests on a simple observation: it suffices to round the times at which machines become free, rather than the times at which jobs start, to a grid whose width is proportional to the job size, and an optimal policy stretched by a factor close to one already respects such grids. We also show that every policy that fixes the order of the jobs in advance loses a factor $Ω(\log N)$, already on two machines, so a constant factor requires adapting the order to the observed outcomes. Further results include a polynomial-time adaptive rule with ratio $\min\{m,1+\sum_j q_j\}$, a simpler approximation scheme for a constant number of sizes, and #P-hardness of computing the optimal expected cost on two machines.

Friday, October 09 2026, 00:00

$Ω((\log n/\log\log n)^2)$ Lower Bounds for Dynamic Graph Problems

Authors: Young Kun Ko

We prove an $Ω((\log n/\log\log n)^2)$ unconditional lower bound on the maximum of the query time and update time for dynamic data structures supporting reachability queries in $n$-node directed acyclic graphs under edge insertions. This improves the $\widetildeΩ(\log^{3/2} n)$ lower bound of Larsen and Yu [SICOMP 2025], and matches the strongest lower bound known for any dynamic problem. The same bound holds for incremental undirected shortest paths and subgraph connectivity. To prove it, we bring the recent framework of Ko [FOCS 2026], which gave this bound for Pătraşcu's multiphase problem with Inner Product, to the multiphase problem with Disjointness. Our main technical contribution is to show that verification in Ko's 2.5-round multiphase communication game makes a one-sided corruption bound suffice in place of discrepancy, which Disjointness lacks.

Authors: Young Kun Ko

We prove an $Ω((\log n/\log\log n)^2)$ unconditional lower bound on the maximum of the query time and update time for dynamic data structures supporting reachability queries in $n$-node directed acyclic graphs under edge insertions. This improves the $\widetildeΩ(\log^{3/2} n)$ lower bound of Larsen and Yu [SICOMP 2025], and matches the strongest lower bound known for any dynamic problem. The same bound holds for incremental undirected shortest paths and subgraph connectivity. To prove it, we bring the recent framework of Ko [FOCS 2026], which gave this bound for Pătraşcu's multiphase problem with Inner Product, to the multiphase problem with Disjointness. Our main technical contribution is to show that verification in Ko's 2.5-round multiphase communication game makes a one-sided corruption bound suffice in place of discrepancy, which Disjointness lacks.

Friday, October 09 2026, 00:00

The Geometry of Hierarchical Navigation: Accuracy and Query Cost for Point Process Input

Authors: Shankar Bhamidi, Souvik Dhara, Lars Schroeder, Clara Stegehuis

Large-scale information retrieval systems, including retrieval-augmented generation (RAG) and recommendation engines, widely use multi-layered hierarchical data structures for ultra-fast approximate nearest-neighbor search in high-dimensional vector spaces. However, the geometric conditions that ensure accurate and efficient greedy navigation remain poorly understood. In this work, we study the efficiency of greedy navigation on a hierarchy of proximity graphs constructed from $n$ data points on the $d$-dimensional torus~$\mathbb{T}^d$. We identify a deterministic coverage condition under which, given any query $q\in \mathbb{T}^d$, greedy search returns a point within $(1+\varepsilon)$-factor of the distance to the closest point. This coverage property holds with high probability when the data is distributed as a homogeneous Poisson process, a Hermitian determinantal process, or a bounded-density Cox process, as long as $d = o(\log n/\log \log n)$. Under the same assumptions, the expected number of greedy hops for a fixed query is $O\!\left(\exp\!\left(\tfrac12 d\log d+O(d)\right)\log n\right)$, yielding logarithmic expected hop count in fixed dimension.

Authors: Shankar Bhamidi, Souvik Dhara, Lars Schroeder, Clara Stegehuis

Large-scale information retrieval systems, including retrieval-augmented generation (RAG) and recommendation engines, widely use multi-layered hierarchical data structures for ultra-fast approximate nearest-neighbor search in high-dimensional vector spaces. However, the geometric conditions that ensure accurate and efficient greedy navigation remain poorly understood. In this work, we study the efficiency of greedy navigation on a hierarchy of proximity graphs constructed from $n$ data points on the $d$-dimensional torus~$\mathbb{T}^d$. We identify a deterministic coverage condition under which, given any query $q\in \mathbb{T}^d$, greedy search returns a point within $(1+\varepsilon)$-factor of the distance to the closest point. This coverage property holds with high probability when the data is distributed as a homogeneous Poisson process, a Hermitian determinantal process, or a bounded-density Cox process, as long as $d = o(\log n/\log \log n)$. Under the same assumptions, the expected number of greedy hops for a fixed query is $O\!\left(\exp\!\left(\tfrac12 d\log d+O(d)\right)\log n\right)$, yielding logarithmic expected hop count in fixed dimension.

Friday, October 09 2026, 00:00

Peeling Half the Onion: Embedding $k$-Outerplanar Graphs into $\ell_1$ and Trees with a Polynomial Distortion (in $k$)

Authors: Hsien-Chih Chang, Jonathan Conroy, William Eliot, Hung Le, Vinayak

Chekuri, Gupta, Newman, Rabinovich, and Sinclair [SODA'03] showed that $k$-outerplanar graphs can be embedded into trees and $\ell_1$ with distortion $2^{O(k)}$. Their result is perhaps the strongest evidence supporting the still-open planar $\ell_1$-embedding conjecture: planar metrics can be embedded into $\ell_1$ with constant distortion. However, the exponential dependency on $k$ in their distortion bound remains the state of the art. Their embedding is obtained by a so-called onion-peeling approach: removing one layer of the graph at a time at the cost of incurring $O(1)$ distortion multiplicatively, and recursively embedding the resulting $(k-1)$-outerplanar graph. In this paper, we devise a new onion peeling approach that peels $k/2$ layers off the input $k$-outerplanar graph at every step. As a result, we obtain the first embedding of $k$-outerplanar graphs into trees and $\ell_1$ with distortion $\operatorname{poly}(k)$, an exponential improvement over the best-known distortion bound [SODA'03]. Our result of embeddings into trees comes closer to the distortion lower bound $Ω(k)$ for $k$-outerplanar graphs.

Authors: Hsien-Chih Chang, Jonathan Conroy, William Eliot, Hung Le, Vinayak

Chekuri, Gupta, Newman, Rabinovich, and Sinclair [SODA'03] showed that $k$-outerplanar graphs can be embedded into trees and $\ell_1$ with distortion $2^{O(k)}$. Their result is perhaps the strongest evidence supporting the still-open planar $\ell_1$-embedding conjecture: planar metrics can be embedded into $\ell_1$ with constant distortion. However, the exponential dependency on $k$ in their distortion bound remains the state of the art. Their embedding is obtained by a so-called onion-peeling approach: removing one layer of the graph at a time at the cost of incurring $O(1)$ distortion multiplicatively, and recursively embedding the resulting $(k-1)$-outerplanar graph. In this paper, we devise a new onion peeling approach that peels $k/2$ layers off the input $k$-outerplanar graph at every step. As a result, we obtain the first embedding of $k$-outerplanar graphs into trees and $\ell_1$ with distortion $\operatorname{poly}(k)$, an exponential improvement over the best-known distortion bound [SODA'03]. Our result of embeddings into trees comes closer to the distortion lower bound $Ω(k)$ for $k$-outerplanar graphs.

Friday, October 09 2026, 00:00

Deterministic Distance Selection in $O(n^{4/3})$ Time

Authors: Haitao Wang

Let $P$ be a set of $n$ points in the plane. Given an integer $K$ with $1\le K\le {n\choose 2}$, the distance selection problem asks for the $K$-th smallest distance among all pairwise distances of the points of $P$. The problem has been studied extensively over the past four decades. Recently, Chan and Zheng (2023) gave a randomized algorithm with $O(n^{4/3})$ expected running time, while the best known deterministic algorithm runs in $O(n^{4/3}\log n)$ time. In this paper, we present a deterministic $O(n^{4/3})$-time algorithm for the problem, matching the best known randomized complexity. We also consider the more general bichromatic version of the problem, where two point sets $A$ and $B$ are given, with $m=|A|$ and $n=|B|$, and the goal is to find the $K$-th smallest distance among the $mn$ distances between points of $A$ and points of $B$. For this problem, the best previously known algorithm runs in $O((m\log n+n\log m+m^{2/3}n^{2/3})\log(m+n))$ time. We present a new deterministic algorithm with running time $O(m\log^2 n+n\log^2 m+m^{2/3}n^{2/3})$.

Authors: Haitao Wang

Let $P$ be a set of $n$ points in the plane. Given an integer $K$ with $1\le K\le {n\choose 2}$, the distance selection problem asks for the $K$-th smallest distance among all pairwise distances of the points of $P$. The problem has been studied extensively over the past four decades. Recently, Chan and Zheng (2023) gave a randomized algorithm with $O(n^{4/3})$ expected running time, while the best known deterministic algorithm runs in $O(n^{4/3}\log n)$ time. In this paper, we present a deterministic $O(n^{4/3})$-time algorithm for the problem, matching the best known randomized complexity. We also consider the more general bichromatic version of the problem, where two point sets $A$ and $B$ are given, with $m=|A|$ and $n=|B|$, and the goal is to find the $K$-th smallest distance among the $mn$ distances between points of $A$ and points of $B$. For this problem, the best previously known algorithm runs in $O((m\log n+n\log m+m^{2/3}n^{2/3})\log(m+n))$ time. We present a new deterministic algorithm with running time $O(m\log^2 n+n\log^2 m+m^{2/3}n^{2/3})$.

Friday, October 09 2026, 00:00

Coupling Independence Implies Zero-Freeness

Authors: Shuai Shao, Ke Shi

For $Δ\ge2$ and $q\ge11Δ/6$, we prove that the antiferromagnetic $q$-state Potts partition function on finite simple graphs of maximum degree at most $Δ$ has no Fisher zeros in a graph-uniform complex neighbourhood of $[0,1]$. For $q>11Δ/6$, the proof establishes coupling independence throughout $[0,1]$ using a soft version of Vigoda's flip dynamics. Our main tool is a separator-shell transfer theorem for the Potts model on induced-subgraph closed classes of graphs of maximum degree at most $Δ$, with $q\geΔ+1$. It yields a graph-uniform zero-free neighbourhood of $[0,1]$ from Hamming coupling independence at $0$ and a uniform coupling-independence bound on each interval $[δ,1]$, $δ\in(0,1]$. We also obtain zero-free Lee-Yang polydiscs around the uniform field for vertex- and edge-colour fields. For Boolean Holant problems on bounded-degree graphs whose signatures come from a fixed finite family of log-concave symmetric signatures $f$ with $f(0)>0$, such as $b$-matchings, we obtain graph-uniform zero-free polytubes around every bounded box of nonnegative activities; their union is an open zero-free neighbourhood of the nonnegative orthant. An appendix summarizes further coupling-independence inputs and the zero-free regions they yield.

Authors: Shuai Shao, Ke Shi

For $Δ\ge2$ and $q\ge11Δ/6$, we prove that the antiferromagnetic $q$-state Potts partition function on finite simple graphs of maximum degree at most $Δ$ has no Fisher zeros in a graph-uniform complex neighbourhood of $[0,1]$. For $q>11Δ/6$, the proof establishes coupling independence throughout $[0,1]$ using a soft version of Vigoda's flip dynamics. Our main tool is a separator-shell transfer theorem for the Potts model on induced-subgraph closed classes of graphs of maximum degree at most $Δ$, with $q\geΔ+1$. It yields a graph-uniform zero-free neighbourhood of $[0,1]$ from Hamming coupling independence at $0$ and a uniform coupling-independence bound on each interval $[δ,1]$, $δ\in(0,1]$. We also obtain zero-free Lee-Yang polydiscs around the uniform field for vertex- and edge-colour fields. For Boolean Holant problems on bounded-degree graphs whose signatures come from a fixed finite family of log-concave symmetric signatures $f$ with $f(0)>0$, such as $b$-matchings, we obtain graph-uniform zero-free polytubes around every bounded box of nonnegative activities; their union is an open zero-free neighbourhood of the nonnegative orthant. An appendix summarizes further coupling-independence inputs and the zero-free regions they yield.

Friday, October 09 2026, 00:00

Parallel Edge Ranking of Trees

Authors: Jeff Giliberti, MohammadTaghi Hajiaghayi, Changki Yun

In this work, we prove that computing the edge ranking of a tree in parallel is P-Complete. An optimal tree edge ranking assigns positive integer ranks to the edges such that any two edges with the same rank are separated by an edge of higher rank, while minimizing the highest rank. Tree edge ranking abstracts several classical problems such as parallel assembly in manufacturing, minimum-height dendrograms, reversible pebble game and edge-query binary search on trees. Its parallel complexity remained open for over thirty years, since the seminal work of de la Torre, Greenlaw, and Sch{ä}ffer [SODA'93], and was listed as an open problem in the book Limits to Parallel Computation by Greenlaw, Hoover, and Ruzzo [1995]. We prove that deciding whether a tree has edge ranking at most $K$ is P-Complete, already for trees of diameter six. Our reduction is from NOR-CVP and simulates a greedy procedure underlying known sequential approaches. Despite ruling out NC algorithms, we prove that this hardness barrier can be bypassed in the well-known model of Massively Parallel Computation (MPC) with strongly sublinear local memory, showing that $O(\log n)$ MPC rounds suffice to solve the hard tree-edge ranking instances used to prove P-Completeness. Specifically, we present a deterministic MPC algorithm that computes an optimal edge ranking of an $n$-vertex tree of diameter $D$ in $O(\log D+\log\log n)$ rounds with $O(n^{3/4}D^{1/4})$ local memory. Our algorithm circumvents the linear-memory barrier by compressing the information required to produce a lexicographically minimal ranking from subtree merges. Overall, this result reinforces the strict separation between NC and what can be computed efficiently in MPC.

Authors: Jeff Giliberti, MohammadTaghi Hajiaghayi, Changki Yun

In this work, we prove that computing the edge ranking of a tree in parallel is P-Complete. An optimal tree edge ranking assigns positive integer ranks to the edges such that any two edges with the same rank are separated by an edge of higher rank, while minimizing the highest rank. Tree edge ranking abstracts several classical problems such as parallel assembly in manufacturing, minimum-height dendrograms, reversible pebble game and edge-query binary search on trees. Its parallel complexity remained open for over thirty years, since the seminal work of de la Torre, Greenlaw, and Sch{ä}ffer [SODA'93], and was listed as an open problem in the book Limits to Parallel Computation by Greenlaw, Hoover, and Ruzzo [1995]. We prove that deciding whether a tree has edge ranking at most $K$ is P-Complete, already for trees of diameter six. Our reduction is from NOR-CVP and simulates a greedy procedure underlying known sequential approaches. Despite ruling out NC algorithms, we prove that this hardness barrier can be bypassed in the well-known model of Massively Parallel Computation (MPC) with strongly sublinear local memory, showing that $O(\log n)$ MPC rounds suffice to solve the hard tree-edge ranking instances used to prove P-Completeness. Specifically, we present a deterministic MPC algorithm that computes an optimal edge ranking of an $n$-vertex tree of diameter $D$ in $O(\log D+\log\log n)$ rounds with $O(n^{3/4}D^{1/4})$ local memory. Our algorithm circumvents the linear-memory barrier by compressing the information required to produce a lexicographically minimal ranking from subtree merges. Overall, this result reinforces the strict separation between NC and what can be computed efficiently in MPC.

Friday, October 09 2026, 00:00

A Computationally-Efficient Closed-Form $C^{s,1}$-Extension Formula

Authors: Anastasis Kratsios, Philipp Zimmermann

We identify explicit closed-form and variational formulae for interpolating the exact values and derivatives through order $s$ of a $C^{s,1}$ function $f:\mathbb{R}^d\to\mathbb{R}$ at $N$ distinct points in $[0,1]^d$. The reconstruction satisfies bounds on its global $C^{s,1}$ seminorm and its Lipschitz constant on $[0,1]^d$ that are independent of the sample size $N$, the latter being the sharp Whitney condition. For $s\ge2$, the reconstruction is real analytic away from the data points and definable in the o-minimal structure $\mathbb{R}_{\exp}$. Our nonlinear extension formula coincides with the formula of McShane (1934) for $s=0$ and with the formulae of Le Gruyer and Phan (2015) and Azagra, Le Gruyer, and Mudarra (2018) for $s=1$, and is new for $s\ge2$. For fixed $d$ and $s\ge2$, our closed-form formula is computable away from the data points by a circuit using only elementary unary and binary real operations, with $\mathcal{O}(N)$ gates and $\mathcal{O}(\log N)$ depth. This yields $\mathcal{O}(N)$ storage and $\mathcal{O}(\log N)$ parallel evaluation time. From the supplied coefficients and weights, the circuit can be compiled with $\mathcal{O}(N)$ one-time work in the exact-real word-RAM model. Thus, in this supplied-data setting, our nonlinear construction improves by a logarithmic factor on the $\mathcal{O}(N\log N)$ initialization bound of Fefferman and Klartag (2009), while retaining linear storage and attaining logarithmic query time through parallel evaluation.

Authors: Anastasis Kratsios, Philipp Zimmermann

We identify explicit closed-form and variational formulae for interpolating the exact values and derivatives through order $s$ of a $C^{s,1}$ function $f:\mathbb{R}^d\to\mathbb{R}$ at $N$ distinct points in $[0,1]^d$. The reconstruction satisfies bounds on its global $C^{s,1}$ seminorm and its Lipschitz constant on $[0,1]^d$ that are independent of the sample size $N$, the latter being the sharp Whitney condition. For $s\ge2$, the reconstruction is real analytic away from the data points and definable in the o-minimal structure $\mathbb{R}_{\exp}$. Our nonlinear extension formula coincides with the formula of McShane (1934) for $s=0$ and with the formulae of Le Gruyer and Phan (2015) and Azagra, Le Gruyer, and Mudarra (2018) for $s=1$, and is new for $s\ge2$. For fixed $d$ and $s\ge2$, our closed-form formula is computable away from the data points by a circuit using only elementary unary and binary real operations, with $\mathcal{O}(N)$ gates and $\mathcal{O}(\log N)$ depth. This yields $\mathcal{O}(N)$ storage and $\mathcal{O}(\log N)$ parallel evaluation time. From the supplied coefficients and weights, the circuit can be compiled with $\mathcal{O}(N)$ one-time work in the exact-real word-RAM model. Thus, in this supplied-data setting, our nonlinear construction improves by a logarithmic factor on the $\mathcal{O}(N\log N)$ initialization bound of Fefferman and Klartag (2009), while retaining linear storage and attaining logarithmic query time through parallel evaluation.

Friday, October 09 2026, 00:00

Improved Approximations for Vehicle Routing with Nonuniform Speeds

Authors: Hong Li

We study vehicle routing with vehicles of different speeds on a complete undirected graph whose vertex set consists of a depot and a set of clients, where the distances satisfy the triangle inequality. Each vehicle has a specified speed, and if the total length traveled by a vehicle of speed $s$ is $L$, its completion time is $L/s$. In the heterogeneous traveling salesman problem (HetTSP), each vehicle executes one tour starting and ending at the depot, and the tours collectively visit all clients. The objective is to minimize the maximum completion time among the vehicles. We give a $6$-approximation algorithm for HetTSP, improving the previous $90(1+δ)$-approximation for any fixed $δ>0$. We also consider two versions of the heterogeneous capacitated vehicle routing problem (HetCVRP). Each client has a demand, and the vehicles have identical capacities. A vehicle may execute several tours, each starting and ending at the depot, and reload at the depot between consecutive tours; the total demand delivered on each tour cannot exceed the vehicle capacity. In the split-delivery version of HetCVRP, the demand of a client may be divided among multiple visits, possibly by different vehicles. We give a $\frac92+2\sqrt3<7.965$-approximation algorithm for this problem. In the unsplit-delivery version of HetCVRP, the entire demand of each client must be delivered in a single visit. We give a $\frac{11}{2}+3\sqrt2<9.743$-approximation algorithm, improving the previous $450(1+δ)$-approximation for any fixed $δ>0$.

Authors: Hong Li

We study vehicle routing with vehicles of different speeds on a complete undirected graph whose vertex set consists of a depot and a set of clients, where the distances satisfy the triangle inequality. Each vehicle has a specified speed, and if the total length traveled by a vehicle of speed $s$ is $L$, its completion time is $L/s$. In the heterogeneous traveling salesman problem (HetTSP), each vehicle executes one tour starting and ending at the depot, and the tours collectively visit all clients. The objective is to minimize the maximum completion time among the vehicles. We give a $6$-approximation algorithm for HetTSP, improving the previous $90(1+δ)$-approximation for any fixed $δ>0$. We also consider two versions of the heterogeneous capacitated vehicle routing problem (HetCVRP). Each client has a demand, and the vehicles have identical capacities. A vehicle may execute several tours, each starting and ending at the depot, and reload at the depot between consecutive tours; the total demand delivered on each tour cannot exceed the vehicle capacity. In the split-delivery version of HetCVRP, the demand of a client may be divided among multiple visits, possibly by different vehicles. We give a $\frac92+2\sqrt3<7.965$-approximation algorithm for this problem. In the unsplit-delivery version of HetCVRP, the entire demand of each client must be delivered in a single visit. We give a $\frac{11}{2}+3\sqrt2<9.743$-approximation algorithm, improving the previous $450(1+δ)$-approximation for any fixed $δ>0$.

Friday, October 09 2026, 00:00

Escaping Degeneracy by Following Shadow Edges

Authors: Alexander E. Black, Sean Kafer, Laura Sanità

The Simplex method is among the most widely used approaches for solving linear programs. Starting at a vertex solution of the feasible region, the algorithm proceeds through a sequence of basis exchanges (known as pivots), each corresponding to a move along an improving edge of the polyhedron toward a better vertex. A central challenge affecting the efficiency of the Simplex method is degeneracy, which can cause long sequences of pivot operations that fail to change the current vertex solution. In this paper, we prove the existence of a pivot rule which is able to escape degeneracy and follow any given shadow edge-direction when initialized at some compatible basis, with a linear number of degenerate Simplex pivots. As a byproduct of our result, we obtain an improved bound on the number of degenerate Simplex pivots needed to solve linear programs defined on 0/1 polytopes.

Authors: Alexander E. Black, Sean Kafer, Laura Sanità

The Simplex method is among the most widely used approaches for solving linear programs. Starting at a vertex solution of the feasible region, the algorithm proceeds through a sequence of basis exchanges (known as pivots), each corresponding to a move along an improving edge of the polyhedron toward a better vertex. A central challenge affecting the efficiency of the Simplex method is degeneracy, which can cause long sequences of pivot operations that fail to change the current vertex solution. In this paper, we prove the existence of a pivot rule which is able to escape degeneracy and follow any given shadow edge-direction when initialized at some compatible basis, with a linear number of degenerate Simplex pivots. As a byproduct of our result, we obtain an improved bound on the number of degenerate Simplex pivots needed to solve linear programs defined on 0/1 polytopes.

Friday, October 09 2026, 00:00

Faster Directed Hopsets, Distance Preservers, and Deterministic Shortcut Sets

Authors: Ben Bals, Daniel Dadush, Gary Hoppenworth, Yasamin Nazari, Rajath Rao K. N

While there have been many recent advances in getting better tradeoffs for directed distance structures such as hopsets, shortcut sets and distance preservers, most known algorithms are inefficient. In this work we provide three results: - Faster algorithms for directed $(1+ε)$-hopsets, matching the state-of-the-art size/hopbound trade-offs of Bernstein & Wein [SODA23]. Our algorithm is first designed for DAGs and then extended to general graphs (up to $n^{o(1)}$ factors) using the recent DAG projection result of Haeupler, Jiang, and Saranurak [STOC26]. - Faster \textit{deterministic} algorithms for constructing shortcut sets, matching the state-of-the-art size/hopbound tradeoffs of Kogan & Parter [SODA22A]. - Using our improved directed hopset construction, we get significantly faster algorithms for computing source-wise distance preservers. This algorithm is based on speeding-up reductions of Kogan & Parter [SODA22B] by using certain structural properties of our hopsets.

Authors: Ben Bals, Daniel Dadush, Gary Hoppenworth, Yasamin Nazari, Rajath Rao K. N

While there have been many recent advances in getting better tradeoffs for directed distance structures such as hopsets, shortcut sets and distance preservers, most known algorithms are inefficient. In this work we provide three results: - Faster algorithms for directed $(1+ε)$-hopsets, matching the state-of-the-art size/hopbound trade-offs of Bernstein & Wein [SODA23]. Our algorithm is first designed for DAGs and then extended to general graphs (up to $n^{o(1)}$ factors) using the recent DAG projection result of Haeupler, Jiang, and Saranurak [STOC26]. - Faster \textit{deterministic} algorithms for constructing shortcut sets, matching the state-of-the-art size/hopbound tradeoffs of Kogan & Parter [SODA22A]. - Using our improved directed hopset construction, we get significantly faster algorithms for computing source-wise distance preservers. This algorithm is based on speeding-up reductions of Kogan & Parter [SODA22B] by using certain structural properties of our hopsets.

Friday, October 09 2026, 00:00

Faster Planar Graph Algorithms for Connectivity Problems via Meanders

Authors: Susanna Caroppo, Giordano Da Lozzo, Giuseppe Di Battista, Jevgēnijs Vihrovs

In this paper, we refine the dynamic programming framework based on the sphere cut decomposition designed by Dorn, Penninkx, Bodlaender, and Fomin (ESA 2005) to obtain faster subexponential algorithms for connectivity problems on planar graphs. We investigate the relationship between these problems and meanders, which are simple closed planar loops that intersect a fixed line in a given number of points. By combining dynamic programming with techniques from meandric system analysis and the use of fast matrix multiplication by Dorn (ESA 2006), we obtain improved algorithms for planar connectivity problems. We show that the number of meanders on $2n$ crossings $M_n$ is $\mathcal O^*(12.806^n)$, which improves the previous upper bound of $\mathcal O^*(12.901^n)$ by Albert and Paterson (FPSAC 2004). This then gives the best-known classical upper bounds on the deterministic time complexity of several planar graph problems with polynomially-bounded weights, namely $\mathcal O(2^{5.543\sqrt n})$ for the Planar Travelling Salesman problem, $\mathcal O(2^{5.796\sqrt n})$ for Planar Longest Cycle/Path, $\mathcal O(2^{8.251\sqrt n})$ for Planar Connected Dominating Set and $\mathcal O(2^{8.037\sqrt n})$ for Planar Steiner Tree. Notably, this leads to the best-known deterministic complexity $\mathcal O(2^{5.543\sqrt{n}})$ for the Planar Hamiltonian Cycle problem.

Authors: Susanna Caroppo, Giordano Da Lozzo, Giuseppe Di Battista, Jevgēnijs Vihrovs

In this paper, we refine the dynamic programming framework based on the sphere cut decomposition designed by Dorn, Penninkx, Bodlaender, and Fomin (ESA 2005) to obtain faster subexponential algorithms for connectivity problems on planar graphs. We investigate the relationship between these problems and meanders, which are simple closed planar loops that intersect a fixed line in a given number of points. By combining dynamic programming with techniques from meandric system analysis and the use of fast matrix multiplication by Dorn (ESA 2006), we obtain improved algorithms for planar connectivity problems. We show that the number of meanders on $2n$ crossings $M_n$ is $\mathcal O^*(12.806^n)$, which improves the previous upper bound of $\mathcal O^*(12.901^n)$ by Albert and Paterson (FPSAC 2004). This then gives the best-known classical upper bounds on the deterministic time complexity of several planar graph problems with polynomially-bounded weights, namely $\mathcal O(2^{5.543\sqrt n})$ for the Planar Travelling Salesman problem, $\mathcal O(2^{5.796\sqrt n})$ for Planar Longest Cycle/Path, $\mathcal O(2^{8.251\sqrt n})$ for Planar Connected Dominating Set and $\mathcal O(2^{8.037\sqrt n})$ for Planar Steiner Tree. Notably, this leads to the best-known deterministic complexity $\mathcal O(2^{5.543\sqrt{n}})$ for the Planar Hamiltonian Cycle problem.

Friday, October 09 2026, 00:00

Local Sensitivity in Exponential Selection: Failure Modes and Valid Calibrations

Authors: Dung Nguyen, Anil Vullikanti

Selection is a task that chooses one element from a finite public candidate range to maximize a data-dependent score. In differential privacy (DP), the exponential mechanism (EM) samples a candidate at a temperature calibrated to the global sensitivity. In this paper, we study when dataset-dependent sensitivity can safely replace global sensitivity in private selection. We propose three valid approaches. First, a private, high-probability upper bound on local sensitivity yields approximate DP, and the method extends to finite higher-order sensitivity hierarchies. Second, our Propose-Test-Release (PTR) variant privately searches a finite public grid for a temperature scale rather than fixing it in advance. Third, smooth sensitivity supports several designs. A candidate-independent smooth geometric construction produces a sensitivity envelope that is admissible under the local dampening framework, which privacy is guaranteed for any admissible envelope. Additionally, a separate logarithmic transformation utilizes smooth sensitivity to produce a smoothed candidate score function with advantages: having controlled global sensitivity, and preserving the maximizers of the original utility score, i.e., candidates maximizing the utility. Both of the designs yield range-independent pure DP. Besides that, we also give two approximate DP private selectors using smooth sensitivity: a direct EM with smooth sensitivity calibrated to the candidate range and privacy parameters that matches a theoretical lower bound up to some constant factor, and one using a privatized smooth upper scale by analyzing the logarithmic transform of the smoothness. For every proposed mechanism, we derive a high-probability regret bound under its stated conditions.

Authors: Dung Nguyen, Anil Vullikanti

Selection is a task that chooses one element from a finite public candidate range to maximize a data-dependent score. In differential privacy (DP), the exponential mechanism (EM) samples a candidate at a temperature calibrated to the global sensitivity. In this paper, we study when dataset-dependent sensitivity can safely replace global sensitivity in private selection. We propose three valid approaches. First, a private, high-probability upper bound on local sensitivity yields approximate DP, and the method extends to finite higher-order sensitivity hierarchies. Second, our Propose-Test-Release (PTR) variant privately searches a finite public grid for a temperature scale rather than fixing it in advance. Third, smooth sensitivity supports several designs. A candidate-independent smooth geometric construction produces a sensitivity envelope that is admissible under the local dampening framework, which privacy is guaranteed for any admissible envelope. Additionally, a separate logarithmic transformation utilizes smooth sensitivity to produce a smoothed candidate score function with advantages: having controlled global sensitivity, and preserving the maximizers of the original utility score, i.e., candidates maximizing the utility. Both of the designs yield range-independent pure DP. Besides that, we also give two approximate DP private selectors using smooth sensitivity: a direct EM with smooth sensitivity calibrated to the candidate range and privacy parameters that matches a theoretical lower bound up to some constant factor, and one using a privatized smooth upper scale by analyzing the logarithmic transform of the smoothness. For every proposed mechanism, we derive a high-probability regret bound under its stated conditions.

Friday, October 09 2026, 00:00

Deterministic Approximation of the Total Variation Distance Between Spin Systems

Authors: Zelin Li, Minji Yang

We study deterministic relative approximation of the total variation distance between two Gibbs distributions induced by spin systems on the same bounded-degree graph. For the hard-core model, we give a deterministic polynomial-time $\varepsilon$-relative-error approximation when both external-field vectors lie in $[b,(1-η)λ_{\mathrm c}(Δ)]^V$, where $b>0$ and $η\in(0,1)$ are fixed and $λ_{\mathrm c}(Δ)$ is the hard-core uniqueness threshold. For the Ising model, we obtain deterministic polynomial-time algorithms in two settings: the ferromagnetic Lee--Yang regime and the antiferromagnetic correlation-decay regime. We develop a new deterministic framework that reduces this task to estimating suitably chosen partition functions.

Authors: Zelin Li, Minji Yang

We study deterministic relative approximation of the total variation distance between two Gibbs distributions induced by spin systems on the same bounded-degree graph. For the hard-core model, we give a deterministic polynomial-time $\varepsilon$-relative-error approximation when both external-field vectors lie in $[b,(1-η)λ_{\mathrm c}(Δ)]^V$, where $b>0$ and $η\in(0,1)$ are fixed and $λ_{\mathrm c}(Δ)$ is the hard-core uniqueness threshold. For the Ising model, we obtain deterministic polynomial-time algorithms in two settings: the ferromagnetic Lee--Yang regime and the antiferromagnetic correlation-decay regime. We develop a new deterministic framework that reduces this task to estimating suitably chosen partition functions.

Friday, October 09 2026, 00:00

Efficient Recovery of Latent Coordinate Structure from Sparse Observations of the Hypercube

Authors: Rares-Darius Buhai, Davide Mazzali, Weronika Wrzos-Kaminska

Recovering latent geometric structure from graph observations is a well-studied problem in statistical inference. Kapralov, Trevisan, and Wrzos-Kaminska (2026) introduced the problem of recovering the coordinate structure of the Boolean hypercube from a small random sample of its edges. More specifically, there are $n=2^d$ vertices, each corresponding to a distinct "feature" vector in $\{\pm 1\}^d$. Between each pair whose feature vectors are at Hamming distance one, an edge is observed independently with probability $p$. As long as the expected degree $pd$ is $\gtrsim \log d = \log \log n$, we give a polynomial-time algorithm that, given only the graph of observed edges, correctly recovers the entire feature vector of all but a vanishing fraction of vertices. This matches the information-theoretic guarantee of Kapralov, Trevisan, and Wrzos-Kaminska in polynomial rather than exponential time, resolving the algorithmic question left open by their work. Our algorithm combines a degree-$4$ sum-of-squares certificate for the structure of balanced near-minimum cuts with a rounding scheme originally developed for tensor decomposition by Ma, Shi, and Steurer (2016). The analysis relies on two novel ingredients: a sum-of-squares version of the Friedgut-Kalai-Naor theorem in Boolean Fourier analysis and a spectral concentration result for the observed subgraph of the hypercube. Finally, we provide a justification for why higher-degree sum-of-squares might be needed by showing a limitation of the basic SDP relaxation of this problem.

Authors: Rares-Darius Buhai, Davide Mazzali, Weronika Wrzos-Kaminska

Recovering latent geometric structure from graph observations is a well-studied problem in statistical inference. Kapralov, Trevisan, and Wrzos-Kaminska (2026) introduced the problem of recovering the coordinate structure of the Boolean hypercube from a small random sample of its edges. More specifically, there are $n=2^d$ vertices, each corresponding to a distinct "feature" vector in $\{\pm 1\}^d$. Between each pair whose feature vectors are at Hamming distance one, an edge is observed independently with probability $p$. As long as the expected degree $pd$ is $\gtrsim \log d = \log \log n$, we give a polynomial-time algorithm that, given only the graph of observed edges, correctly recovers the entire feature vector of all but a vanishing fraction of vertices. This matches the information-theoretic guarantee of Kapralov, Trevisan, and Wrzos-Kaminska in polynomial rather than exponential time, resolving the algorithmic question left open by their work. Our algorithm combines a degree-$4$ sum-of-squares certificate for the structure of balanced near-minimum cuts with a rounding scheme originally developed for tensor decomposition by Ma, Shi, and Steurer (2016). The analysis relies on two novel ingredients: a sum-of-squares version of the Friedgut-Kalai-Naor theorem in Boolean Fourier analysis and a spectral concentration result for the observed subgraph of the hypercube. Finally, we provide a justification for why higher-degree sum-of-squares might be needed by showing a limitation of the basic SDP relaxation of this problem.

Friday, October 09 2026, 00:00

A Refined Analysis for Matroid Secretary with Submodular Objectives

Authors: Dennis Joyce

We study the matroid secretary problem with a nonnegative monotone submodular objective. Elements arrive in uniformly random order, and every acceptance decision is immediate and irrevocable. We give an $8.699$-competitive algorithm for arbitrary matroids. The algorithm first rejects a randomly sized initial segment of the arrival sequence as a learning set and runs submodular greedy on all elements in this set. Each later element receives a fixed weight equal to the marginal value it would have when inserted into the stored greedy sequence. On these fixed weights, the algorithm runs a linear-objective matroid secretary subroutine. The algorithm uses $O(nr)$ value queries and $O(n^2)$ independence queries, where $r$ is the matroid rank.

Authors: Dennis Joyce

We study the matroid secretary problem with a nonnegative monotone submodular objective. Elements arrive in uniformly random order, and every acceptance decision is immediate and irrevocable. We give an $8.699$-competitive algorithm for arbitrary matroids. The algorithm first rejects a randomly sized initial segment of the arrival sequence as a learning set and runs submodular greedy on all elements in this set. Each later element receives a fixed weight equal to the marginal value it would have when inserted into the stored greedy sequence. On these fixed weights, the algorithm runs a linear-objective matroid secretary subroutine. The algorithm uses $O(nr)$ value queries and $O(n^2)$ independence queries, where $r$ is the matroid rank.

Friday, October 09 2026, 00:00

An ETH-based quasipolynomial lower bound for Dualization

Authors: Yasuaki Kobayashi, Kazuhiro Kurita, Kunihiro Wasa

Dualizing monotone Boolean functions (or equivalently, enumerating minimal transversals in hypergraphs) is a long-standing problem whose output-polynomial-time solvability remains open. While various special cases have been extensively studied, the state-of-the-art algorithm for the general case, due to Fredman and Khachiyan, runs in quasipolynomial time. This paper presents a subexponential-time reduction from \textsc{3SAT} to the complement of \textsc{Dual}: Given a 3CNF formula with $n$ variables, the reduction constructs hypergraphs $\mathcal H$ and $\mathcal L$ of total size $2^{\bigoh(n^{2/3}(\log n)^{1/3})}$ such that $\mathcal L \subseteq \Tr(\mathcal H)$ and the formula is satisfiable if and only if $\mathcal L\neq \Tr(\mathcal H)$. As a consequence of this reduction, assuming the Exponential Time Hypothesis (ETH), neither \textsc{Dual} nor \textsc{Dualization} admits an algorithm running in $N^{o(\sqrt{\log N/\log\log N})}$ time, where $N$ is the input size for \textsc{Dual} and the combined input and output size for \textsc{Dualization}. In particular, \textsc{Dualization} cannot be solved in output-polynomial time under ETH.

Authors: Yasuaki Kobayashi, Kazuhiro Kurita, Kunihiro Wasa

Dualizing monotone Boolean functions (or equivalently, enumerating minimal transversals in hypergraphs) is a long-standing problem whose output-polynomial-time solvability remains open. While various special cases have been extensively studied, the state-of-the-art algorithm for the general case, due to Fredman and Khachiyan, runs in quasipolynomial time. This paper presents a subexponential-time reduction from \textsc{3SAT} to the complement of \textsc{Dual}: Given a 3CNF formula with $n$ variables, the reduction constructs hypergraphs $\mathcal H$ and $\mathcal L$ of total size $2^{\bigoh(n^{2/3}(\log n)^{1/3})}$ such that $\mathcal L \subseteq \Tr(\mathcal H)$ and the formula is satisfiable if and only if $\mathcal L\neq \Tr(\mathcal H)$. As a consequence of this reduction, assuming the Exponential Time Hypothesis (ETH), neither \textsc{Dual} nor \textsc{Dualization} admits an algorithm running in $N^{o(\sqrt{\log N/\log\log N})}$ time, where $N$ is the input size for \textsc{Dual} and the combined input and output size for \textsc{Dualization}. In particular, \textsc{Dualization} cannot be solved in output-polynomial time under ETH.

Friday, October 09 2026, 00:00

The chromatic number of the associahedron: simple and logarithmic

Authors: Benjamin Aram Berendsohn, Jean Cardinal, John Iacono, László Kozma

Addario-Berry, Reed, Scott, and Wood (JoCG 2026) proved that the $n$-dimensional associahedron has chromatic number at most $22500\cdot\log_3 n+O(1)$. We present a much simpler proof that the chromatic number of the $n-1$-dimensional associahedron is at most $6 \log_2 n + 18$. Since this paper's appearance as a preliminary abstract in the Japan Conference on Discrete and Computational Geometry, Graphs, and Games held from September 7-10, 2026, the bound has been improved to $O(\log \log n)$ by Oum and Wood (arXiv September 30, 2026). It is hoped that the simple method here could give insights to further improvements.

Authors: Benjamin Aram Berendsohn, Jean Cardinal, John Iacono, László Kozma

Addario-Berry, Reed, Scott, and Wood (JoCG 2026) proved that the $n$-dimensional associahedron has chromatic number at most $22500\cdot\log_3 n+O(1)$. We present a much simpler proof that the chromatic number of the $n-1$-dimensional associahedron is at most $6 \log_2 n + 18$. Since this paper's appearance as a preliminary abstract in the Japan Conference on Discrete and Computational Geometry, Graphs, and Games held from September 7-10, 2026, the bound has been improved to $O(\log \log n)$ by Oum and Wood (arXiv September 30, 2026). It is hoped that the simple method here could give insights to further improvements.

Friday, October 09 2026, 00:00

Tight bounds and output sensitive algorithms for maximal clique enumeration in link streams

Authors: George Manoussakis

A link stream is a set of interactions between pairs of vertices, each one lasting during some time interval, and a clique of a link stream is a set of vertices together with a time interval during which all of them interact. A clique is maximal if neither its vertex set nor its interval can be enlarged. All known algorithms listing the maximal cliques of a link stream may spend time exponential in the size of a clique for each clique they output. Here, we approach the question under the light of two parameters of the instantaneous graphs of the stream, their maximum degree $Δ$ and their degeneracy $k$. We prove that a link stream with $m$ links has $O(mΔ^2 3^{Δ/3})$ maximal cliques, and that a link stream with $n$ vertices and $|\mathcal{T}|$ distinct end times has $O(n|\mathcal{T}|k^2 3^{k/3})$ maximal cliques. Both bounds are tight up to a factor polynomial in $Δ$ and $k$ respectively, and the second one improves the factor $2^k$ of previous bounds to $3^{k/3}$. Then we present two algorithms. The first one has setup time $O(m\log m)$ and polynomial time delay $\mathrm{poly}(Δ)\log m$. The second one has setup time $O(m\log m+mk^2\log^3 n)$ and polynomial time delay $\mathrm{poly}(k)\log m$. To the best of our knowledge, these are the first algorithms with polynomial time delay for this problem. We also give an online version of the second algorithm, and we show that our results apply to the $Δ$-cliques and $(Δ,γ)$-cliques of temporal graphs.

Authors: George Manoussakis

A link stream is a set of interactions between pairs of vertices, each one lasting during some time interval, and a clique of a link stream is a set of vertices together with a time interval during which all of them interact. A clique is maximal if neither its vertex set nor its interval can be enlarged. All known algorithms listing the maximal cliques of a link stream may spend time exponential in the size of a clique for each clique they output. Here, we approach the question under the light of two parameters of the instantaneous graphs of the stream, their maximum degree $Δ$ and their degeneracy $k$. We prove that a link stream with $m$ links has $O(mΔ^2 3^{Δ/3})$ maximal cliques, and that a link stream with $n$ vertices and $|\mathcal{T}|$ distinct end times has $O(n|\mathcal{T}|k^2 3^{k/3})$ maximal cliques. Both bounds are tight up to a factor polynomial in $Δ$ and $k$ respectively, and the second one improves the factor $2^k$ of previous bounds to $3^{k/3}$. Then we present two algorithms. The first one has setup time $O(m\log m)$ and polynomial time delay $\mathrm{poly}(Δ)\log m$. The second one has setup time $O(m\log m+mk^2\log^3 n)$ and polynomial time delay $\mathrm{poly}(k)\log m$. To the best of our knowledge, these are the first algorithms with polynomial time delay for this problem. We also give an online version of the second algorithm, and we show that our results apply to the $Δ$-cliques and $(Δ,γ)$-cliques of temporal graphs.

Friday, October 09 2026, 00:00

Tight Bounds for Equivalence Testing with Non-Adaptive Conditional Samples

Authors: Gautam Kamath

We study distribution testing with access to non-adaptive conditional samples. Specifically, we give tight bounds for equivalence testing, determining whether two unknown distributions are equal to or $\varepsilon$-far from each other in total variation distance. Our algorithm and lower bound show that $\tilde Θ\left(\frac{\log n}{\varepsilon^2}\right)$ queries are necessary and sufficient for this problem. These results demonstrate that the complexity of uniformity, identity, and equivalence testing with non-adaptive conditional samples are all $\tilde Θ(\log n)$.

Authors: Gautam Kamath

We study distribution testing with access to non-adaptive conditional samples. Specifically, we give tight bounds for equivalence testing, determining whether two unknown distributions are equal to or $\varepsilon$-far from each other in total variation distance. Our algorithm and lower bound show that $\tilde Θ\left(\frac{\log n}{\varepsilon^2}\right)$ queries are necessary and sufficient for this problem. These results demonstrate that the complexity of uniformity, identity, and equivalence testing with non-adaptive conditional samples are all $\tilde Θ(\log n)$.

Friday, October 09 2026, 00:00

Non-Clairvoyant Scheduling is Hard Even for Trees

Authors: Kunal Agrawal, Owen Druzgal, Milind Prabhu, Jinhao Zhao

We study online scheduling of parallel jobs on $m$ identical processors to minimize maximum flow time. Each arriving job is represented by a directed acyclic graph (DAG) whose vertices are unit-time subjobs and whose edges specify precedence constraints. We consider non-clairvoyant algorithms: the DAG is not known when a job arrives, and each subjob is revealed only when it becomes ready. Agrawal, Moseley, Newman, and Pruhs (SPAA 2024) showed that First-In-First-Out (FIFO) has competitive ratio $Ω(\log m)$ even when every job is an out-tree. They also proved that FIFO is $O(\log m)$-competitive in several natural settings and asked whether this guarantee extends to general instances. More broadly, they asked whether any non-clairvoyant algorithm can be $O(1)$-competitive. We answer both questions in the negative by proving a lower bound of $Ω(\min\{m,\mathrm{OPT}\})$ for every non-clairvoyant online algorithm, where $\mathrm{OPT}$ is the maximum flow time of an optimal offline schedule. In particular, every non-clairvoyant algorithm has competitive ratio $Ω(m)$ on some instance with $\mathrm{OPT} \ge m$. The lower bound holds even when every job is an out-forest. We complement these lower bounds with an asymptotically optimal non-clairvoyant algorithm. FIFO is $O(m)$-competitive, but can have competitive ratio $Ω(m)$ even when $\mathrm{OPT}=O(1)$. For instances with small $\mathrm{OPT}$, we design a Small-Frontier-First algorithm that is $O(\mathrm{OPT})$-competitive. Combining the two algorithms yields an $O(\min\{m,\mathrm{OPT}\})$-competitive non-clairvoyant algorithm.

Authors: Kunal Agrawal, Owen Druzgal, Milind Prabhu, Jinhao Zhao

We study online scheduling of parallel jobs on $m$ identical processors to minimize maximum flow time. Each arriving job is represented by a directed acyclic graph (DAG) whose vertices are unit-time subjobs and whose edges specify precedence constraints. We consider non-clairvoyant algorithms: the DAG is not known when a job arrives, and each subjob is revealed only when it becomes ready. Agrawal, Moseley, Newman, and Pruhs (SPAA 2024) showed that First-In-First-Out (FIFO) has competitive ratio $Ω(\log m)$ even when every job is an out-tree. They also proved that FIFO is $O(\log m)$-competitive in several natural settings and asked whether this guarantee extends to general instances. More broadly, they asked whether any non-clairvoyant algorithm can be $O(1)$-competitive. We answer both questions in the negative by proving a lower bound of $Ω(\min\{m,\mathrm{OPT}\})$ for every non-clairvoyant online algorithm, where $\mathrm{OPT}$ is the maximum flow time of an optimal offline schedule. In particular, every non-clairvoyant algorithm has competitive ratio $Ω(m)$ on some instance with $\mathrm{OPT} \ge m$. The lower bound holds even when every job is an out-forest. We complement these lower bounds with an asymptotically optimal non-clairvoyant algorithm. FIFO is $O(m)$-competitive, but can have competitive ratio $Ω(m)$ even when $\mathrm{OPT}=O(1)$. For instances with small $\mathrm{OPT}$, we design a Small-Frontier-First algorithm that is $O(\mathrm{OPT})$-competitive. Combining the two algorithms yields an $O(\min\{m,\mathrm{OPT}\})$-competitive non-clairvoyant algorithm.

Friday, October 09 2026, 00:00

Smallest String Attractors and Minimal Coverage Certificates of Thue--Morse Words

Authors: Simone Faro, Francesco Pio Marino, Arianna Pavone

String attractors provide a compact way of representing the complete factor structure of a word: a set of positions is an attractor if every distinct factor has at least one occurrence crossing one of the selected positions. Although the minimum attractor size is known for several classical families of words, describing \emph{all} optimal attractors is typically much more difficult, since it requires understanding the geometry of all factor occurrences rather than constructing a single optimal solution. We give a complete description for the finite Thue--Morse words. Earlier work proved that four positions are necessary and sufficient for every order $n\geq 4$, but the collection of all smallest attractors remained unknown. For every $n\geq 6$, writing $h=2^{n-3}$, we prove that the smallest attractors are exactly the two reflected families where the four offsets are chosen independently from $\{0,1\}$. Hence there are exactly $32$ smallest attractors for every $n\geq6$. The initial cases are genuinely exceptional: $t_5$ has $40$ smallest attractors and $t_4$ has $87$. We also study the attractor condition independently of optimality. For every $n\geq5$, we characterize the complete antichain of inclusion-minimal factor coverages of $t_n$. It consists precisely of the coverages of $aa$, $bb$, and the eight minimal unique substrings of every generation $t_m$, $4\leq m\leq n$. Thus there are exactly $8n-22$ canonical constraints, forming an irredundant exact certificate for attractors of arbitrary cardinality. When attention is restricted to four-position sets, this linear-size system collapses to a constant one: it is enough to test the $24$ minimal unique substrings coming from three consecutive generations, and sixteen of these already force the two optimal families. We also show that three generations are necessary within this natural consecutive-generation hierarchy.

Authors: Simone Faro, Francesco Pio Marino, Arianna Pavone

String attractors provide a compact way of representing the complete factor structure of a word: a set of positions is an attractor if every distinct factor has at least one occurrence crossing one of the selected positions. Although the minimum attractor size is known for several classical families of words, describing \emph{all} optimal attractors is typically much more difficult, since it requires understanding the geometry of all factor occurrences rather than constructing a single optimal solution. We give a complete description for the finite Thue--Morse words. Earlier work proved that four positions are necessary and sufficient for every order $n\geq 4$, but the collection of all smallest attractors remained unknown. For every $n\geq 6$, writing $h=2^{n-3}$, we prove that the smallest attractors are exactly the two reflected families where the four offsets are chosen independently from $\{0,1\}$. Hence there are exactly $32$ smallest attractors for every $n\geq6$. The initial cases are genuinely exceptional: $t_5$ has $40$ smallest attractors and $t_4$ has $87$. We also study the attractor condition independently of optimality. For every $n\geq5$, we characterize the complete antichain of inclusion-minimal factor coverages of $t_n$. It consists precisely of the coverages of $aa$, $bb$, and the eight minimal unique substrings of every generation $t_m$, $4\leq m\leq n$. Thus there are exactly $8n-22$ canonical constraints, forming an irredundant exact certificate for attractors of arbitrary cardinality. When attention is restricted to four-position sets, this linear-size system collapses to a constant one: it is enough to test the $24$ minimal unique substrings coming from three consecutive generations, and sixteen of these already force the two optimal families. We also show that three generations are necessary within this natural consecutive-generation hierarchy.

Friday, October 09 2026, 00:00

Directed Global Minimum Cut in Almost-Linear Time

Authors: Henry Fleischmann, Jason Li, Thatchaphol Saranurak, Benyu Wang

We give a randomized reduction from global minimum cut in a directed graph with $n$ vertices and $m$ weighted edges to maximum-flow computations on graphs of total size $\widetilde{O}(m)$. For polynomially bounded integral weights, this yields the first almost-linear $m^{1+o(1)}$-time algorithm [vdBCK+23], improving the previous $m^{1+o(1)}\min\{\sqrt{n},n/m^{1/3}\}$ bound [CLN+22]. Previous work reduced finding the minimum cut to constructing a 1-respecting arborescence, a directed spanning tree with exactly one edge crossing a minimum cut [CLN+22]. They then construct such a tree by sampling from a $(1+ε)$-approximate arborescence packing, which currently requires superlinear time. Our algorithm sidesteps constructing the packing entirely and relies on a novel iterative arborescence sampling procedure. We show that, after $O(\log n)$ rounds of sampling, our final arborescence 1-respects the minimum cut with constant probability.

Authors: Henry Fleischmann, Jason Li, Thatchaphol Saranurak, Benyu Wang

We give a randomized reduction from global minimum cut in a directed graph with $n$ vertices and $m$ weighted edges to maximum-flow computations on graphs of total size $\widetilde{O}(m)$. For polynomially bounded integral weights, this yields the first almost-linear $m^{1+o(1)}$-time algorithm [vdBCK+23], improving the previous $m^{1+o(1)}\min\{\sqrt{n},n/m^{1/3}\}$ bound [CLN+22]. Previous work reduced finding the minimum cut to constructing a 1-respecting arborescence, a directed spanning tree with exactly one edge crossing a minimum cut [CLN+22]. They then construct such a tree by sampling from a $(1+ε)$-approximate arborescence packing, which currently requires superlinear time. Our algorithm sidesteps constructing the packing entirely and relies on a novel iterative arborescence sampling procedure. We show that, after $O(\log n)$ rounds of sampling, our final arborescence 1-respects the minimum cut with constant probability.

Friday, October 09 2026, 00:00

Unimaginative Uncertainty

from Ben Recht

How most uncertainty can’t be quantified.

Hi there, argmin readers! Today’s post is a live blog of Class 11 of my graduate seminar “Forecasting: A Critical Retrospective.” The syllabus and list of past posts are here.

In “Communicating Uncertainty in Policy Analysis,” Charles Manski takes to the Proceedings of the National Academy of Sciences to chastise government officials for their failure to report uncertainty in their forecasts. Now, what would that reporting look like? We need the uncertainty reports to be clear, legible, and objective. Being good bureaucrats, those desiderata tell us we need to quantify our uncertainty.

Sadly, our technocratic imagination for what uncertainty quantification means is woefully narrow. Uncertainty quantification almost exclusively means error bars. In this case of forecasts, an error bar specifically means a prediction interval. A prediction interval is a probabilistic object. It quantizes a forecast of some numerical quantity into a discrete binary event. Rather than saying I think GDP will grow by 3% in the first quarter of 2027, I say, “The chance that GDP will grow between 0 and 7% in the first quarter of 2027 is 95%.” Based on your modeling, you believe some measurement will lie in some band with some probability.

Even our methods to construct these prediction intervals lack creativity. 95% of the time, we build those intervals by assuming the data is Gaussian, estimating the variance, and then setting the bounds to be plus or minus two sigma. That variance estimate might come from direct analysis of the model. For example, if you assume linear dynamics perturbed by Gaussian shocks, you can compute the variance exactly.

For more complicated models, you might get the variance from Monte Carlo simulation or estimate it from past data. For example, in weather forecasting, you could generate error bars by sampling a bunch of likely atmospheric states, propagating them through a complex simulation, and then computing quantiles. Other methods bin past prediction errors, arguing that this isolates aleatoric uncertainty from epistemic uncertainty, then build error bars from those so-called “innovations.”1 If you want to be really fancy and pretend you are avoiding assumptions about distributions, you can just compute 95% quantiles directly from the observed errors.

And that’s more or less all of the tricks we know. How many classes must we spend on it? How many papers must we write about it?2 In this class, we’ll only use one.

I’m always left with the uncomfortable problem that I have no idea what to do with probabilistic error bars. Usually what “probability” means is incredibly sloppily specified in these models. Even in the constructions I described above, the probability is dependent on an unverifiable chain of modeling decisions, and there’s no way to doubly quantify the uncertainty in my modeling. A good engineer will just multiply their error bars by 2 and call it a day.

For better or for worse, however, forecasters are not always engineers. They just might want to use the uncertainty to hedge their bets. If they turn their numerical estimate into a probabilistic one, they can’t be wrong. Conveniently, probabilistic predictions of binary events are more easily scored by our standard proper scoring rules.

Outside narrow forecasting contests, it’s unclear how reporting an interval changes policy decisions. In weather forecasting, you can give people a sense of whether they should bring an umbrella. But error bars on growth are harder to parse from a decision-theoretic standpoint. Yet these are, perhaps unsurprisingly, exactly the sorts of uncertainty reports Manski calls for:

“For example, the CBO could report the 0.10 and 0.90 quantiles of the distribution of potential outcomes that it referenced when scoring the American Health Care Act of 2017. Alternately, it could present a full probabilistic forecast in a graphical fan chart, such as the Bank of England uses to predict GDP growth (see the discussion later in this article).”

Perhaps you can say that all that matters is the sign of GDP growth: negative growth is bad, and positive growth is good. This leads to a self-fulfilling prophecy in macroeconomic planning. When they estimate a negative number, economists declare a recession, and everyone gets mad. The problem, of course, is that many countries have positive GDP growth right now, and people are still pissed off. Making policy where their forecast sign is correct didn’t solve the current administration’s political problems.

Anyway, I’ve written about my disdain for this blindered approach to uncertainty quantification before, and every time I come back to how we always want something else. People want a prefactual analysis for what we should do if our story is wrong. They want to know how we will recover from failures, and articulating the vast complexity of uncertainty might help with such preparation. Halfway through this class on forecasting, my knee-jerk conclusion is that these are what most serious forecasters want too! In Manski’s long list of sources of uncertainty, only a couple can be quantified. However, holistic reporting of uncertainty can prepare us for what the model doesn’t say and help us think about what to do when our forecasts inevitably miss the mark.

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1

Innovation is such a wild name for prediction error.

2

A Google Scholar search of “conformal prediction” says the answer is thousands.

By Ben Recht

Thursday, October 08 2026, 17:00

TR26-236 | Error-Correction of Matrix Multiplication Algorithms over Integers | Shuichi Hirahara, Nobutaka Shimizu

from ECCC Papers

Suppose there is an oracle $\mathcal{O}$ that computes a tiny fraction of the entries of the product of two uniformly random binary matrices over integers. We prove that there is a nearly linear-size randomized $\mathcal{O}$-oracle circuit that, with high probability, computes all the entries of the product of every pair of binary matrices. This extends the previous ``worst-case exact to average-case approximate'' reduction of Hirahara and Shimizu (STOC 2025), which assumes the average-case distribution to be uniformly random matrices over a finite field, to uniformly random binary matrices. The technical core of our reduction is an approximate list-decoding procedure for a signed sum encoding of the matrix product over the integers based on expander walks. To decode this encoding, we combine the near-linear-time approximation algorithm for MAX $k$-CSP supported on splittable tuples by Jeronimo (RANDOM 2023) with the XOR lemma for multi-output functions by Hirahara and Shimizu (STOC 2025).

Thursday, October 08 2026, 14:52

TR26-235 | The One-and-a-Half Johnson Bound Is Tight for Proximity Gaps of General Linear Codes | Scott Duke Kominers, Justin Thaler, Kai Zhe Zheng

from ECCC Papers

For a linear code $C\subseteq\mathbb{F}_q^n$, we say that $C$ satisfies the \emph{proximity-gaps property} up to distance $\delta_1$ if, for every $\delta_2>\delta_1$ and every $f,g\in\mathbb{F}_q^n$, at least one of which is $\delta_2$-far from $C$ in relative Hamming distance, there are only a small fraction (typically at most $\operatorname{poly}(n)/q$) of \emph{exceptional coefficients} $z\in\mathbb{F}_q$ for which $f+zg$ is $\delta_1$-close to $C$. Prior work shows that every linear code of relative distance $\delta$ satisfies proximity gaps up to the one-and-a-half Johnson radius $J_{3/2}(\delta)=1-(1-\delta)^{1/3}$. We prove that this threshold is tight at every distance $0<\delta<1$ for general linear codes. Specifically, for every $0<\delta<1$, we construct a linear code of relative distance arbitrarily close to $\delta$ and words $f,g$ that are both $\left(1-(1-\delta)^{4/9}\right)$-far from the code, but have a constant fraction of coefficients $z$ for which $f+zg$ is nearly $J_{3/2}(\delta)$-close to the code. Our counterexamples continue to hold even when a fixed amount of distance-dependent slack is allowed.

Thursday, October 08 2026, 14:50

TR26-234 | Deterministic Parameterized Inapproximability of Nearest Codeword and Minimum Distance | Venkatesan Guruswami, Xuandi Ren

from ECCC Papers

We show that the nearest-codeword and minimum-distance problems for linear codes over every fixed finite field are W[1]-hard to approximate within any constant factor under deterministic fixed-parameter many-one reductions. This gives unconditional deterministic parameterized inapproximability for minimum distance, including the binary problem usually called Even Set. The reduction starts from exact nearest codeword and produces a constant gap directly. Over $\mathbb{F}_q$ with $q>2$, an input of length $m$ and threshold $k$ gives instances with threshold $q^k$ and length $O_q(q^k m)$. Tensor products amplify the gap, and a simple concatenation handles codes over $\mathbb{F}_2$.

Thursday, October 08 2026, 14:45

Primal/Dual Method for the Grothendieck Constant

Authors: Steven Heilman, Chris Jones, Giulio Malavolta

We determine the hundredths digit of the real Grothendieck constant by proving $1.773 \leq K_G \leq 1.7799$. Furthermore, numerical heuristics suggest the estimate $K_G \approx 1.779$. We start by simplifying the Gaussian duality theory of $K_G$, based on Hermite projection games and Krivine rounding schemes. The bounds are obtained by a heuristic primal/dual search for these objects, followed by rigorous {\em certification} of their values. The search and certification are performed using AI tools, and in particular the rigorous certificates are very large (analytical reductions to thousands of numerical inequalities).

Authors: Steven Heilman, Chris Jones, Giulio Malavolta

We determine the hundredths digit of the real Grothendieck constant by proving $1.773 \leq K_G \leq 1.7799$. Furthermore, numerical heuristics suggest the estimate $K_G \approx 1.779$. We start by simplifying the Gaussian duality theory of $K_G$, based on Hermite projection games and Krivine rounding schemes. The bounds are obtained by a heuristic primal/dual search for these objects, followed by rigorous {\em certification} of their values. The search and certification are performed using AI tools, and in particular the rigorous certificates are very large (analytical reductions to thousands of numerical inequalities).

Thursday, October 08 2026, 00:00

The smallest programmable machine and the hardness of analyzing it

Authors: J. Andres Montoya

We investigate the computational complexity of analyzing the structural and behavioral properties of deterministic k-pebble automata, which represent a natural framework for studying minimal programmable machines. First, we provide an explicit construction of a three-pebble automaton U capable of simulating any deterministic finite automaton (DFA) on a given input word, establishing a link between pebble automata capabilities, Kolmogorov complexity, and automatic complexity. Next, we restrict our architectural framework to two-pebble programmable machines U(2,N) simulating DFAs with at most N states. We analyze the decision problem ANAL(U(2,5)), which asks whether a five-state program can separate two distinct finite words. By establishing a polynomial-time reduction from the quasi-identity checking problem for finite semigroups, we prove that ANAL(U(2,5)) is NP-complete. Finally, we explore the complexity of separating binary strings under the Exponential Time Hypothesis (ETH), showing how computational hardness implies polynomial lower bounds for the size of the smallest DFAs separating binary strings.

Authors: J. Andres Montoya

We investigate the computational complexity of analyzing the structural and behavioral properties of deterministic k-pebble automata, which represent a natural framework for studying minimal programmable machines. First, we provide an explicit construction of a three-pebble automaton U capable of simulating any deterministic finite automaton (DFA) on a given input word, establishing a link between pebble automata capabilities, Kolmogorov complexity, and automatic complexity. Next, we restrict our architectural framework to two-pebble programmable machines U(2,N) simulating DFAs with at most N states. We analyze the decision problem ANAL(U(2,5)), which asks whether a five-state program can separate two distinct finite words. By establishing a polynomial-time reduction from the quasi-identity checking problem for finite semigroups, we prove that ANAL(U(2,5)) is NP-complete. Finally, we explore the complexity of separating binary strings under the Exponential Time Hypothesis (ETH), showing how computational hardness implies polynomial lower bounds for the size of the smallest DFAs separating binary strings.

Thursday, October 08 2026, 00:00

Quantum Approximation Complexity of Classical Optimization Problems

Authors: Stuart Hadfield

Classical approximation complexity asks what solution quality can be guaranteed with polynomial-time computation. The classes APX, PTAS, and FPTAS distinguish a fixed approximation ratio, approximation to any fixed accuracy, and approximation schemes whose running time is also polynomial in inverse accuracy. Their randomized counterparts are R-APX, R-PTAS, and R-FPTAS. We define bounded-error quantum counterparts BQ-APX, BQ-PTAS, and BQ-FPTAS. Membership requires a uniform quantum algorithm that, on every input, returns a feasible classical solution achieving at least the claimed approximation ratio with probability at least 2/3. Scores (objective values) must be efficiently classically computable. Running time includes parameter selection, preparation, measurement, decoding, and repetition. Many quantum optimization methods are used heuristically, and high benchmark scores alone do not establish these guarantees. We further establish a conditional hierarchy for logarithmic, polynomial, and exponential approximation factors. Assuming NP $\nsubseteq$ BQP, the quantum classes form a strict hierarchy. Problems based on prime factorization and discrete logarithms give conditional quantum-classical separations. Certified Maximum Order has an exact quantum algorithm, while any randomized polynomial-time algorithm guaranteeing at least an inverse-polynomial approximation ratio on every input would yield efficient factoring. Discrete-Logarithm Fitting has an exact quantum algorithm and a deterministic one-half approximation, but any fixed improvement over one half would give a randomized polynomial-time algorithm for the safe-prime discrete logarithm problem. Our results show, under explicit complexity assumptions, that quantum computation can improve worst-case approximation guarantees. A quantum-classical gap for common problems such as MaxCut or MaxSAT remains open.

Authors: Stuart Hadfield

Classical approximation complexity asks what solution quality can be guaranteed with polynomial-time computation. The classes APX, PTAS, and FPTAS distinguish a fixed approximation ratio, approximation to any fixed accuracy, and approximation schemes whose running time is also polynomial in inverse accuracy. Their randomized counterparts are R-APX, R-PTAS, and R-FPTAS. We define bounded-error quantum counterparts BQ-APX, BQ-PTAS, and BQ-FPTAS. Membership requires a uniform quantum algorithm that, on every input, returns a feasible classical solution achieving at least the claimed approximation ratio with probability at least 2/3. Scores (objective values) must be efficiently classically computable. Running time includes parameter selection, preparation, measurement, decoding, and repetition. Many quantum optimization methods are used heuristically, and high benchmark scores alone do not establish these guarantees. We further establish a conditional hierarchy for logarithmic, polynomial, and exponential approximation factors. Assuming NP $\nsubseteq$ BQP, the quantum classes form a strict hierarchy. Problems based on prime factorization and discrete logarithms give conditional quantum-classical separations. Certified Maximum Order has an exact quantum algorithm, while any randomized polynomial-time algorithm guaranteeing at least an inverse-polynomial approximation ratio on every input would yield efficient factoring. Discrete-Logarithm Fitting has an exact quantum algorithm and a deterministic one-half approximation, but any fixed improvement over one half would give a randomized polynomial-time algorithm for the safe-prime discrete logarithm problem. Our results show, under explicit complexity assumptions, that quantum computation can improve worst-case approximation guarantees. A quantum-classical gap for common problems such as MaxCut or MaxSAT remains open.

Thursday, October 08 2026, 00:00

Optimal (Parallel) Spooky Pebbling on Binary Trees

Authors: Mingyu Lee, Sanghyun Lee, Kabgyun Jeong

Pebble games model computations under a fixed space budget. Spooky pebbling allows quantum memory to be released by measurement, with the resulting phases corrected later. We study two-input computations with binary-tree dependencies and determine the optimal work and parallel depth for complete binary trees. Our key idea is to clean up the tree in blocks, reducing repeated recomputation of intermediate values. For the complete tree $B_h$ with $n=2^h-1$ vertices and every space budget $h+1\le s\le n$, we give an algorithm with asymptotically optimal work $Θ(nh/\log(s+1))$. At the minimum budget $s=h+1$, this improves the $O(n\log n)$ bound of Kornerup, Sadun, and Soloveichik to $Θ(n\log n/\log\log n)$, resolving their time-optimality question. We also construct a parallel schedule with optimal depth \[ Θ\!\left(h+\frac ns \max\!\left\{\frac{h}{\log(s+1)},\,1+\log^*h\right\}\right). \] Our lower bounds hold for every full binary tree. We also show that achieving optimal parallel depth can require asymptotically more work than minimizing work alone. Applying our schedule to the RNS point-addition trees in the public implementation of Chevignard, Fouque, and Schrottenloher reduces their Toffoli/AND gate count by $20.86\%$ for a P-224 instance and $22.66\%$ for a P-256 instance, using the same arithmetic circuits and peak workspace.

Authors: Mingyu Lee, Sanghyun Lee, Kabgyun Jeong

Pebble games model computations under a fixed space budget. Spooky pebbling allows quantum memory to be released by measurement, with the resulting phases corrected later. We study two-input computations with binary-tree dependencies and determine the optimal work and parallel depth for complete binary trees. Our key idea is to clean up the tree in blocks, reducing repeated recomputation of intermediate values. For the complete tree $B_h$ with $n=2^h-1$ vertices and every space budget $h+1\le s\le n$, we give an algorithm with asymptotically optimal work $Θ(nh/\log(s+1))$. At the minimum budget $s=h+1$, this improves the $O(n\log n)$ bound of Kornerup, Sadun, and Soloveichik to $Θ(n\log n/\log\log n)$, resolving their time-optimality question. We also construct a parallel schedule with optimal depth \[ Θ\!\left(h+\frac ns \max\!\left\{\frac{h}{\log(s+1)},\,1+\log^*h\right\}\right). \] Our lower bounds hold for every full binary tree. We also show that achieving optimal parallel depth can require asymptotically more work than minimizing work alone. Applying our schedule to the RNS point-addition trees in the public implementation of Chevignard, Fouque, and Schrottenloher reduces their Toffoli/AND gate count by $20.86\%$ for a P-224 instance and $22.66\%$ for a P-256 instance, using the same arithmetic circuits and peak workspace.

Thursday, October 08 2026, 00:00

Improving the Constant in the Aharonov--Regev Theorem

Authors: Shuhong Gao

The Aharonov-Regev proof that $\mathrm{GapCVP}_{c\sqrt n}$ lies in $\mathsf{NP}\cap \mathsf{coNP}$ uses a verifier that tests dual lattice vectors; its proof gives $c=100$. We study this verifier through a linear program in which a certificate is modeled as a sample from a probability distribution on the dual lattice. This viewpoint gives an exact analysis of the close-target tests: adding gradient and Hessian checks increases the certified close radius from $σ^{-1}/4$ to $σ^{-1}\sqrt{3/16}$, and higher derivatives cannot improve it within this framework. With Gaussian certificates for far targets, we obtain $$\mathrm{GapCVP}_{c\sqrt n},\ \mathrm{GapSVP}_{c\sqrt n}\in \mathsf{NP} \cap\mathsf{coNP}$$ for every $c>2/(π\sqrt3)\approx0.3676$. An appendix gives a finite-bit implementation of the verifier. We also show that the Gaussian certificate is not always optimal and solve the unbounded-support program exactly for targets of order two, where its value is determined by the spectral capacity of an odd dual coset.

Authors: Shuhong Gao

The Aharonov-Regev proof that $\mathrm{GapCVP}_{c\sqrt n}$ lies in $\mathsf{NP}\cap \mathsf{coNP}$ uses a verifier that tests dual lattice vectors; its proof gives $c=100$. We study this verifier through a linear program in which a certificate is modeled as a sample from a probability distribution on the dual lattice. This viewpoint gives an exact analysis of the close-target tests: adding gradient and Hessian checks increases the certified close radius from $σ^{-1}/4$ to $σ^{-1}\sqrt{3/16}$, and higher derivatives cannot improve it within this framework. With Gaussian certificates for far targets, we obtain $$\mathrm{GapCVP}_{c\sqrt n},\ \mathrm{GapSVP}_{c\sqrt n}\in \mathsf{NP} \cap\mathsf{coNP}$$ for every $c>2/(π\sqrt3)\approx0.3676$. An appendix gives a finite-bit implementation of the verifier. We also show that the Gaussian certificate is not always optimal and solve the unbounded-support program exactly for targets of order two, where its value is determined by the spectral capacity of an odd dual coset.

Thursday, October 08 2026, 00:00

Breaking the Space Barrier and its Application to Language Model Inference

Authors: Arip Asadulaev

Language models are more and more often asked for structured output: JSON that follows a schema, or a tool call with typed arguments. A small machine, an automaton, enforces the format by forbidding the tokens that would break it. We observe that this machine has a rare property: from any of its states, each token leads along exactly one path. Graphs in which only a few paths join any two points are a classical object of complexity theory, and our theoretical result settles an open question about them: one can decide whether such a graph connects two points while verifying that it really has few paths, with very little memory. Precisely, the problem lies in the classes ReachUL, LOGDCFL, C=L and SC2, and needs only O(log2 n/ log log n) space, below the classical O(log2 n) of Savitch's theorem. The constructions behind the proofs become an inference engine: text the format forces is written without running the model, the mask is recomputed on the GPU without any table, recursive formats use a small stack, every output stays valid under a token limit, and independent fields are decoded in parallel and verified. On one 16 GB Apple M2 Pro with Qwen3.5-2B and 4B, against MLX with llguidance, the standard setup for this hardware, schema-constrained extraction finishes 1.2- 1.3x sooner with the same answers, a grammar costs 3 MB instead of up to 1.5 GB, one server holds sixteen grammars where tables run out of memory, and sixteen tool-calling agents finish 2.5x sooner.

Authors: Arip Asadulaev

Language models are more and more often asked for structured output: JSON that follows a schema, or a tool call with typed arguments. A small machine, an automaton, enforces the format by forbidding the tokens that would break it. We observe that this machine has a rare property: from any of its states, each token leads along exactly one path. Graphs in which only a few paths join any two points are a classical object of complexity theory, and our theoretical result settles an open question about them: one can decide whether such a graph connects two points while verifying that it really has few paths, with very little memory. Precisely, the problem lies in the classes ReachUL, LOGDCFL, C=L and SC2, and needs only O(log2 n/ log log n) space, below the classical O(log2 n) of Savitch's theorem. The constructions behind the proofs become an inference engine: text the format forces is written without running the model, the mask is recomputed on the GPU without any table, recursive formats use a small stack, every output stays valid under a token limit, and independent fields are decoded in parallel and verified. On one 16 GB Apple M2 Pro with Qwen3.5-2B and 4B, against MLX with llguidance, the standard setup for this hardware, schema-constrained extraction finishes 1.2- 1.3x sooner with the same answers, a grammar costs 3 MB instead of up to 1.5 GB, one server holds sixteen grammars where tables run out of memory, and sixteen tool-calling agents finish 2.5x sooner.

Thursday, October 08 2026, 00:00

On the Computational Complexity of Hidden Markov Model Identification

Authors: Markel Zubia, Nils Jansen

Identification is the task of recovering the parameters of an unknown ground-truth model from sampled data. When parameters other than the ground truth induce the same output distribution, data alone does not provide enough information to recover the ground truth, and the model is thus called unidentifiable. We study the identifiability problem for hidden Markov models (HMMs): given an HMM, is it identifiable? Existing work on HMM identification establishes conditions under which the ground-truth HMM can be identified. However, most of these conditions are sufficient but not necessary, meaning that, when a model does not satisfy them, its identifiability remains inconclusive. We instead take a computational perspective: is there a sound and complete algorithm that decides whether a given HMM is identifiable, and if so, what is the complexity of this decision problem? We consider the decision problems arising from the various notions of identifiability in the literature, including deterministic, generic, global, local, state-permutation- invariant, and finite-alphabet identifiability. We show that all of these problems are decidable in PSPACE, via reductions to the theory of the reals at various levels of its quantifier-alternation hierarchy. We further show that the deterministic variants are already coETR-hard (and hence coNP-hard) for simply parameterized families.

Authors: Markel Zubia, Nils Jansen

Identification is the task of recovering the parameters of an unknown ground-truth model from sampled data. When parameters other than the ground truth induce the same output distribution, data alone does not provide enough information to recover the ground truth, and the model is thus called unidentifiable. We study the identifiability problem for hidden Markov models (HMMs): given an HMM, is it identifiable? Existing work on HMM identification establishes conditions under which the ground-truth HMM can be identified. However, most of these conditions are sufficient but not necessary, meaning that, when a model does not satisfy them, its identifiability remains inconclusive. We instead take a computational perspective: is there a sound and complete algorithm that decides whether a given HMM is identifiable, and if so, what is the complexity of this decision problem? We consider the decision problems arising from the various notions of identifiability in the literature, including deterministic, generic, global, local, state-permutation- invariant, and finite-alphabet identifiability. We show that all of these problems are decidable in PSPACE, via reductions to the theory of the reals at various levels of its quantifier-alternation hierarchy. We further show that the deterministic variants are already coETR-hard (and hence coNP-hard) for simply parameterized families.

Thursday, October 08 2026, 00:00

Separating comb inequalities is NP-hard

Authors: Yohan Finet, Victor Drouin-Touchette

Comb inequalities are important cutting planes for the symmetric travelling salesman problem, yet the complexity of their exact separation has remained a longstanding question in polyhedral combinatorics. We present a reduction from 3-SAT proving that deciding whether a comb inequality is violated is NP-complete and that the corresponding separation problem is NP-hard. This result holds even when the input vector belongs to the subtour elimination polytope, every edge value is zero, one half or one and the support graph is nonplanar with maximum degree four. The reduction constructs a graph in which six-vertex ladder gadgets encode Boolean relations and cubic graphs enforce consistency among occurrences of each logical variable. For a propositional logic formula with $v$ variables and $m$ clauses, the constructed graph has $40v+70m+30$ vertices and a linear number of positive edges. The reduction also proves hardness when every permitted tooth has two or four vertices with half of the tooth in the handle. We discuss consequences for approximating the maximum comb violation, optimization over the comb relaxation and explain why hardness of separation does not automatically transfer to larger inequality families.

Authors: Yohan Finet, Victor Drouin-Touchette

Comb inequalities are important cutting planes for the symmetric travelling salesman problem, yet the complexity of their exact separation has remained a longstanding question in polyhedral combinatorics. We present a reduction from 3-SAT proving that deciding whether a comb inequality is violated is NP-complete and that the corresponding separation problem is NP-hard. This result holds even when the input vector belongs to the subtour elimination polytope, every edge value is zero, one half or one and the support graph is nonplanar with maximum degree four. The reduction constructs a graph in which six-vertex ladder gadgets encode Boolean relations and cubic graphs enforce consistency among occurrences of each logical variable. For a propositional logic formula with $v$ variables and $m$ clauses, the constructed graph has $40v+70m+30$ vertices and a linear number of positive edges. The reduction also proves hardness when every permitted tooth has two or four vertices with half of the tooth in the handle. We discuss consequences for approximating the maximum comb violation, optimization over the comb relaxation and explain why hardness of separation does not automatically transfer to larger inequality families.

Thursday, October 08 2026, 00:00

Associativity of Multiplication Is Hard for Resolution

Authors: Vincent Liew

SAT solvers are empirically known to perform poorly when reasoning about multiplication. Yet for over a decade we have lacked a theoretical explanation for this phenomenon. CDCL SAT solvers implicitly search for resolution proofs, and no lower bound on proof size has ruled out the existence of short proofs that solvers simply fail to find. We give the first lower bound of this kind by showing that general resolution proofs of the associativity of $n$-bit multiplication require size $2^{Ω((n/\log n)^{1/4})}$. This lower bound holds for a broad class of multiplier encodings based on partial product summation, including the standard array and Wallace-tree multipliers used to bit-blast multiplication in SMT solvers. This result resolves an open problem of Beame and Liew. The proof constructs a reduction from a perfect-matching principle on bounded-degree bipartite expander graphs to multiplier associativity. Itsykson, Slabodkin, and Sokolov proved that this principle is hard for resolution. The lower bound for multiplier associativity follows. The same reduction, when combined with Håstad's recent lower bound for the perfect-matching principle of the odd grid, yields an exponential lower bound for multiplier associativity in the stronger bounded-depth Frege proof systems.

Authors: Vincent Liew

SAT solvers are empirically known to perform poorly when reasoning about multiplication. Yet for over a decade we have lacked a theoretical explanation for this phenomenon. CDCL SAT solvers implicitly search for resolution proofs, and no lower bound on proof size has ruled out the existence of short proofs that solvers simply fail to find. We give the first lower bound of this kind by showing that general resolution proofs of the associativity of $n$-bit multiplication require size $2^{Ω((n/\log n)^{1/4})}$. This lower bound holds for a broad class of multiplier encodings based on partial product summation, including the standard array and Wallace-tree multipliers used to bit-blast multiplication in SMT solvers. This result resolves an open problem of Beame and Liew. The proof constructs a reduction from a perfect-matching principle on bounded-degree bipartite expander graphs to multiplier associativity. Itsykson, Slabodkin, and Sokolov proved that this principle is hard for resolution. The lower bound for multiplier associativity follows. The same reduction, when combined with Håstad's recent lower bound for the perfect-matching principle of the odd grid, yields an exponential lower bound for multiplier associativity in the stronger bounded-depth Frege proof systems.

Thursday, October 08 2026, 00:00

Verification and Self-Improvement in Agentic AI: Foundations and Limits

Authors: Chien-Ping Lu

Agentic AI systems can improve by searching longer, receiving additional support, or modifying how they propose and verify outputs. A performance score does not distinguish these mechanisms. We compare these changes through bounded verification with hidden terminal randomness. A stage specifies admissible transcripts, polynomial bounds, an alternating verification protocol, and a terminal checker. Its native reach uses default support; its closure frontier permits all support already admitted by the interface. Under a uniform pointwise probability gap and task-relative soundness, these are well-defined languages. We prove that independent majority amplification preserves both languages, whereas existential acceptance over random tapes can admit incorrect outputs. Exact verification is the zero-randomness case, with placement and completeness results. The randomized-verifier classes satisfy $Σ_k^{\mathrm{P}}\subseteqΣ_k^{\mathrm{RV}}\subseteqΣ_{k+1}^{\mathrm{P}}$; strict enlargement and depth separation require explicit complexity assumptions, while $\mathrm{BPP}=\mathrm{P}$ yields exact companions with the same frontiers. Representation analysis separates invariant acceptance from core-versus-support labels that can change under refactoring. For recursive self-improvement, uniformly bounded self-modification under a common sound interpreter and fixed verification protocol remains within the same verification class. A separate conditional-error budget controls false selection across adaptively chosen candidates. A quota-enforced XOR-synthesis family separates unbounded ratios of search success from changes in the accepted languages; exact and probabilistic audits check the resulting evidence requirements. The framework ties self-improvement claims to obligations on correctness, admissible evidence, verification resources, and selection error.

Authors: Chien-Ping Lu

Agentic AI systems can improve by searching longer, receiving additional support, or modifying how they propose and verify outputs. A performance score does not distinguish these mechanisms. We compare these changes through bounded verification with hidden terminal randomness. A stage specifies admissible transcripts, polynomial bounds, an alternating verification protocol, and a terminal checker. Its native reach uses default support; its closure frontier permits all support already admitted by the interface. Under a uniform pointwise probability gap and task-relative soundness, these are well-defined languages. We prove that independent majority amplification preserves both languages, whereas existential acceptance over random tapes can admit incorrect outputs. Exact verification is the zero-randomness case, with placement and completeness results. The randomized-verifier classes satisfy $Σ_k^{\mathrm{P}}\subseteqΣ_k^{\mathrm{RV}}\subseteqΣ_{k+1}^{\mathrm{P}}$; strict enlargement and depth separation require explicit complexity assumptions, while $\mathrm{BPP}=\mathrm{P}$ yields exact companions with the same frontiers. Representation analysis separates invariant acceptance from core-versus-support labels that can change under refactoring. For recursive self-improvement, uniformly bounded self-modification under a common sound interpreter and fixed verification protocol remains within the same verification class. A separate conditional-error budget controls false selection across adaptively chosen candidates. A quota-enforced XOR-synthesis family separates unbounded ratios of search success from changes in the accepted languages; exact and probabilistic audits check the resulting evidence requirements. The framework ties self-improvement claims to obligations on correctness, admissible evidence, verification resources, and selection error.

Thursday, October 08 2026, 00:00

$\exists \mathbb{R} \subseteq \textsf{CH}$

Authors: Alex Meiburg

The existential theory of the reals asks whether polynomial constraints with integer coefficients have a real solution. We give a proof placing this problem in the counting hierarchy. The first argument is intended to expose the essential steps, and a separate analysis lowers the bound to $\exists \mathbb{R}\subseteq\textsf{BPP}^{\textsf C_3\textsf P}\subseteq\textsf C_4\textsf P$, the fourth level of the hierarchy. For each fixed $w$, sentences with $w$ alternating real quantifier blocks lie in $\textsf C_{9w+17}\textsf P$. We then treat exact semidefinite feasibility, PosSLP, square-root sum, geometric real counting, Euler characteristic, and complex feasibility in separate applications. The corresponding bounds include $\textsf{BPP}^{\textsf C_2\textsf P}$ for general SDP, $\textsf{BPP}^{\textsf{PP}}\cap\textsf{P}^{\textsf{NP}^{\textsf{PP}}}$ for PosSLP and square-root sum, and $\textsf{FP}^{\textsf C_4\textsf P}$ for total geometric real counting. Note: These proofs were discovered by ChatGPT after a series of conversations ending on September 29th 2026. A group of researchers has been working to digest the proof, and while the most essential arguments appear correct, we are endeavoring to give this result the treatment it deserves and a proper exposition and development to benefit of the community. However, on October 6th, OpenAI released a very similar result, with a slightly weaker bound. While we work to improve our exposition of this proof, the current version has been uploaded as a service to the community to compare the different proof techniques. While the listed author takes responsibility that the proofs appear to be correct, he has not played a nontrivial role in developing them, and believes the human value will be in good exposition and canonicalization of the results.

Authors: Alex Meiburg

The existential theory of the reals asks whether polynomial constraints with integer coefficients have a real solution. We give a proof placing this problem in the counting hierarchy. The first argument is intended to expose the essential steps, and a separate analysis lowers the bound to $\exists \mathbb{R}\subseteq\textsf{BPP}^{\textsf C_3\textsf P}\subseteq\textsf C_4\textsf P$, the fourth level of the hierarchy. For each fixed $w$, sentences with $w$ alternating real quantifier blocks lie in $\textsf C_{9w+17}\textsf P$. We then treat exact semidefinite feasibility, PosSLP, square-root sum, geometric real counting, Euler characteristic, and complex feasibility in separate applications. The corresponding bounds include $\textsf{BPP}^{\textsf C_2\textsf P}$ for general SDP, $\textsf{BPP}^{\textsf{PP}}\cap\textsf{P}^{\textsf{NP}^{\textsf{PP}}}$ for PosSLP and square-root sum, and $\textsf{FP}^{\textsf C_4\textsf P}$ for total geometric real counting. Note: These proofs were discovered by ChatGPT after a series of conversations ending on September 29th 2026. A group of researchers has been working to digest the proof, and while the most essential arguments appear correct, we are endeavoring to give this result the treatment it deserves and a proper exposition and development to benefit of the community. However, on October 6th, OpenAI released a very similar result, with a slightly weaker bound. While we work to improve our exposition of this proof, the current version has been uploaded as a service to the community to compare the different proof techniques. While the listed author takes responsibility that the proofs appear to be correct, he has not played a nontrivial role in developing them, and believes the human value will be in good exposition and canonicalization of the results.

Thursday, October 08 2026, 00:00

Rubix: Global Correspondence-Free Point Set Alignment through Assignment Geometry

Authors: Subhransu S. Bhattacharjee, Dylan Campbell, Rahul Shome

Procrustes-Wasserstein alignment jointly estimates a matching and rotation without supplied correspondences, but alternating minimization can stop at suboptimal solutions. Rubix solves the equally weighted planar problem globally under squared Euclidean loss. Each matching $σ$ of two centered $n$-point sets defines a complex correlation $z_σ=\sum_i\bar x_i y_{σ(i)}$. Their convex hull is the permutation polygon: supporting vertices give optimal matchings at fixed rotations, and the farthest vertex gives the global alignment. We prove the sharp bound of $n(n-1)$ vertices for $n\ge2$, answering Rote's rotation-assignment open problem. In exact arithmetic, assignment queries recover the polygon in $\mathcal O(n^5)$ operations. Assignment-based bounds extend the approach to three-dimensional rotations and partial matching at a supplied translation through branch-and-bound. On timed MPEG-7 shape pairs, Rubix attains every numerical reference value in 12 ms on average, 50 times faster than a rotation grid at the same accuracy. Its distances improve gravity-aligned matching of real 3D scans, shape retrieval and noisy crystal classification over alternating minimization.

Authors: Subhransu S. Bhattacharjee, Dylan Campbell, Rahul Shome

Procrustes-Wasserstein alignment jointly estimates a matching and rotation without supplied correspondences, but alternating minimization can stop at suboptimal solutions. Rubix solves the equally weighted planar problem globally under squared Euclidean loss. Each matching $σ$ of two centered $n$-point sets defines a complex correlation $z_σ=\sum_i\bar x_i y_{σ(i)}$. Their convex hull is the permutation polygon: supporting vertices give optimal matchings at fixed rotations, and the farthest vertex gives the global alignment. We prove the sharp bound of $n(n-1)$ vertices for $n\ge2$, answering Rote's rotation-assignment open problem. In exact arithmetic, assignment queries recover the polygon in $\mathcal O(n^5)$ operations. Assignment-based bounds extend the approach to three-dimensional rotations and partial matching at a supplied translation through branch-and-bound. On timed MPEG-7 shape pairs, Rubix attains every numerical reference value in 12 ms on average, 50 times faster than a rotation grid at the same accuracy. Its distances improve gravity-aligned matching of real 3D scans, shape retrieval and noisy crystal classification over alternating minimization.

Thursday, October 08 2026, 00:00

Symmetric Submodular Minimization from Comparisons

Authors: James Fox, David P. Woodruff

Given value-oracle access to a symmetric submodular function $f:2^V\to\mathbb{R}$ with $|V|=n$, a nontrivial minimizer can be found using $O(n^3)$ value queries. We study the weaker comparison model, in which a query on $S,T\subseteq V$ reveals only whether $f(S)$ is smaller than, equal to, or larger than $f(T)$. We give a deterministic polynomial-time algorithm that finds a nontrivial minimizer of any symmetric submodular function using $O(n^3)$ comparisons, matching the best-known deterministic value-oracle bound despite not knowing the function values. More generally, the same $O(n^3)$-comparison bound holds for minimization over the nonempty members of any downward-closed family. Our algorithm combines the minimum-capacity ordering recently introduced by Iwata and Konno with the contraction framework of Goemans and Soto. Applying this result to weighted graph cut functions resolves the main open question of Cohen-Addad et al., who gave an $\widetilde{O}(n^3)$-comparison algorithm that runs in exponential time and asked whether a weighted minimum cut can be found in polynomial time using comparisons. For graphs with $m$ edges of integer weight at most $B$, we also give a deterministic polynomial-time algorithm that finds a minimum cut using \[ \widetilde{O}\!\left(n^2+\min\!\left\{mB,\,nB^2\right\}\right) \] comparisons, improving on the $O(n^3)$ bound when $B$ is small. Finally, we show that every randomized algorithm that outputs a minimum cut with probability at least $2/3$ makes $Ω(n \log n)$ expected comparisons in the worst case. Under the stronger assumption that all edge weights are polynomially bounded integers, we obtain an $Ω(n \log \log n)$ expected comparison lower bound. These bounds contrast with the value-oracle model, where no $ω(n)$ lower bound is known even for deterministic algorithms.

Authors: James Fox, David P. Woodruff

Given value-oracle access to a symmetric submodular function $f:2^V\to\mathbb{R}$ with $|V|=n$, a nontrivial minimizer can be found using $O(n^3)$ value queries. We study the weaker comparison model, in which a query on $S,T\subseteq V$ reveals only whether $f(S)$ is smaller than, equal to, or larger than $f(T)$. We give a deterministic polynomial-time algorithm that finds a nontrivial minimizer of any symmetric submodular function using $O(n^3)$ comparisons, matching the best-known deterministic value-oracle bound despite not knowing the function values. More generally, the same $O(n^3)$-comparison bound holds for minimization over the nonempty members of any downward-closed family. Our algorithm combines the minimum-capacity ordering recently introduced by Iwata and Konno with the contraction framework of Goemans and Soto. Applying this result to weighted graph cut functions resolves the main open question of Cohen-Addad et al., who gave an $\widetilde{O}(n^3)$-comparison algorithm that runs in exponential time and asked whether a weighted minimum cut can be found in polynomial time using comparisons. For graphs with $m$ edges of integer weight at most $B$, we also give a deterministic polynomial-time algorithm that finds a minimum cut using \[ \widetilde{O}\!\left(n^2+\min\!\left\{mB,\,nB^2\right\}\right) \] comparisons, improving on the $O(n^3)$ bound when $B$ is small. Finally, we show that every randomized algorithm that outputs a minimum cut with probability at least $2/3$ makes $Ω(n \log n)$ expected comparisons in the worst case. Under the stronger assumption that all edge weights are polynomially bounded integers, we obtain an $Ω(n \log \log n)$ expected comparison lower bound. These bounds contrast with the value-oracle model, where no $ω(n)$ lower bound is known even for deterministic algorithms.

Thursday, October 08 2026, 00:00

Barely Monotone (min,+)-Convolution in Truly Subquadratic Time

Authors: MohammadTaghi Hajiaghayi, Danny Mittal, Saeed Seddighin

The (min,+)-convolution of two sequences A and B of length n is the sequence C with C[k] = min_{i+j=k} (A[i]+B[j]). For bounded inputs, whose entries are integers in {0,...,O(n)}, prior work computes it in truly subquadratic time when the inputs are monotone; the algorithm of Chi, Duan, Xie, and Zhang (STOC 2022) takes expected O~(n^{1.5}) time. We introduce a monotonicity measure ranging from 0 (monotone) to 1/2 (entirely non-monotone): a sequence has monotonicity alpha if it can be partitioned into O(n^alpha) monotone subsequences, and by the Erdos-Szekeres theorem every sequence has monotonicity at most 1/2. We show that truly subquadratic time is achievable even when just one input is barely monotone, that is, has monotonicity 1/2 - Omega(1): if A has monotonicity alpha, we compute the convolution in expected time O~(n^{5/3+2alpha/3}) for every bounded B. If B has monotonicity beta as well, the expected time improves to O~(n^{(3+alpha+beta)/2}), which matches the monotone case for alpha = beta = 0; this algorithm also allows infinite entries placed arbitrarily. We complement these algorithms with fine-grained reductions. Bounded (min,+)-convolution reduces to bounded monotone (min,+)-convolution of length N = O(n^{1.5}), so an O(N^{4/3-eps})-time algorithm for monotone inputs would give an O(n^{2-3eps/2})-time algorithm for bounded inputs. Similarly, entries bounded by n reduce to entries bounded by N^x on sequences of length N = Theta(n^{2/(1+x)}). We also show that if only A has entries in {0,...,M}, we can compute the convolution in O~(n(M+1)) time, and in O~(n^{1.5} sqrt(M)) time if A may also contain +infinity.

Authors: MohammadTaghi Hajiaghayi, Danny Mittal, Saeed Seddighin

The (min,+)-convolution of two sequences A and B of length n is the sequence C with C[k] = min_{i+j=k} (A[i]+B[j]). For bounded inputs, whose entries are integers in {0,...,O(n)}, prior work computes it in truly subquadratic time when the inputs are monotone; the algorithm of Chi, Duan, Xie, and Zhang (STOC 2022) takes expected O~(n^{1.5}) time. We introduce a monotonicity measure ranging from 0 (monotone) to 1/2 (entirely non-monotone): a sequence has monotonicity alpha if it can be partitioned into O(n^alpha) monotone subsequences, and by the Erdos-Szekeres theorem every sequence has monotonicity at most 1/2. We show that truly subquadratic time is achievable even when just one input is barely monotone, that is, has monotonicity 1/2 - Omega(1): if A has monotonicity alpha, we compute the convolution in expected time O~(n^{5/3+2alpha/3}) for every bounded B. If B has monotonicity beta as well, the expected time improves to O~(n^{(3+alpha+beta)/2}), which matches the monotone case for alpha = beta = 0; this algorithm also allows infinite entries placed arbitrarily. We complement these algorithms with fine-grained reductions. Bounded (min,+)-convolution reduces to bounded monotone (min,+)-convolution of length N = O(n^{1.5}), so an O(N^{4/3-eps})-time algorithm for monotone inputs would give an O(n^{2-3eps/2})-time algorithm for bounded inputs. Similarly, entries bounded by n reduce to entries bounded by N^x on sequences of length N = Theta(n^{2/(1+x)}). We also show that if only A has entries in {0,...,M}, we can compute the convolution in O~(n(M+1)) time, and in O~(n^{1.5} sqrt(M)) time if A may also contain +infinity.

Thursday, October 08 2026, 00:00

Taxonomic Classification with Complete Tag Arrays

Authors: Travis Gagie, Gonzalo Navarro

Taxonomic classifiers such as Kraken assign each $k$-mer of a reference database to the lowest common ancestor (LCA) of the genomes containing it, but this works less well as databases grow, because more and more $k$-mers are shared across species. Cliffy (Ahmed, Boucher and Langmead, 2025) instead uses variable-length exact matches found with an r-index, and can list approximately the genera containing each match; on 16S rRNA it is more accurate than Kraken~2, but its index is large and expensive to build. We present KATKA, which finds the maximal exact matches (MEMs) of at least a given length in each read with Boyer--Moore--Li on a run-length compressed suffix array, counts the occurrences of each MEM in each genus exactly with a complete, run-length compressed tag array, and gives each genus credit in proportion to those counts. On the SILVA 16S rRNA database, KATKA's default index takes 1.44\,GB and can be built in minutes on a desktop computer; it classifies a read in 66\,$μ$s with one thread and reaches 93.8\% genus-level accuracy, close to what Cliffy reports for its 9\,GB index. Grammar-compressing the runs of the tag array shrinks the index to 1.04\,GB, at 75\,$μ$s per read. On the same machine and reads, it is more accurate than Kraken~2 (79.3\%) and Tagger (81.7 to 92.8\%, depending on how mates that disagree are scored). Indexing minimizer digests instead of the sequences makes the index three times smaller and classification 1.7 times faster, at a cost of 1.3 points of accuracy. KATKA is available at github.com/TravisGagie/KATKA.

Authors: Travis Gagie, Gonzalo Navarro

Taxonomic classifiers such as Kraken assign each $k$-mer of a reference database to the lowest common ancestor (LCA) of the genomes containing it, but this works less well as databases grow, because more and more $k$-mers are shared across species. Cliffy (Ahmed, Boucher and Langmead, 2025) instead uses variable-length exact matches found with an r-index, and can list approximately the genera containing each match; on 16S rRNA it is more accurate than Kraken~2, but its index is large and expensive to build. We present KATKA, which finds the maximal exact matches (MEMs) of at least a given length in each read with Boyer--Moore--Li on a run-length compressed suffix array, counts the occurrences of each MEM in each genus exactly with a complete, run-length compressed tag array, and gives each genus credit in proportion to those counts. On the SILVA 16S rRNA database, KATKA's default index takes 1.44\,GB and can be built in minutes on a desktop computer; it classifies a read in 66\,$μ$s with one thread and reaches 93.8\% genus-level accuracy, close to what Cliffy reports for its 9\,GB index. Grammar-compressing the runs of the tag array shrinks the index to 1.04\,GB, at 75\,$μ$s per read. On the same machine and reads, it is more accurate than Kraken~2 (79.3\%) and Tagger (81.7 to 92.8\%, depending on how mates that disagree are scored). Indexing minimizer digests instead of the sequences makes the index three times smaller and classification 1.7 times faster, at a cost of 1.3 points of accuracy. KATKA is available at https://github.com/TravisGagie/KATKA.

Thursday, October 08 2026, 00:00

Rectangular matrix multiplication from shared-leg entropy

Authors: Przemyslaw Uznanski

In this note, we extend the analysis underlying a recent matrix-multiplication result by OpenAI to rectangular products and prove that $ω(1,k,1)\le 2$ for $0\le k\le \frac{1}{2}$ and $ω(1,k,1)\le 1+k+\frac{1}{4k}$ for $k\ge \frac{1}{2}$. In particular, $ω(1,\frac{1}{2},1)=2$ and the dual exponent satisfies $α\ge \frac{1}{2}$. We use the shared-leg entropy inequality and polynomial-multiplication degenerations from that work, retaining two-leg symmetry and the orientation of each sector. Logarithmic averaging produces homogeneous auxiliary profiles. Their powered versions have a common asymptotic slope, and bounding their intercepts gives the spectral constraint $b\le 4a(1-a)$. This yields the rectangular curve by tensor-spectrum duality. As an application, Zwick's algorithm for all-pairs shortest paths in directed unweighted graphs runs in $O(n^{2.5})$ time. Combining the rectangular bound with the $(\min,+)$-product improvement of Alman and Vassilevska Williams further gives $O(n^{2.4999})$ running time.

Authors: Przemyslaw Uznanski

In this note, we extend the analysis underlying a recent matrix-multiplication result by OpenAI to rectangular products and prove that $ω(1,k,1)\le 2$ for $0\le k\le \frac{1}{2}$ and $ω(1,k,1)\le 1+k+\frac{1}{4k}$ for $k\ge \frac{1}{2}$. In particular, $ω(1,\frac{1}{2},1)=2$ and the dual exponent satisfies $α\ge \frac{1}{2}$. We use the shared-leg entropy inequality and polynomial-multiplication degenerations from that work, retaining two-leg symmetry and the orientation of each sector. Logarithmic averaging produces homogeneous auxiliary profiles. Their powered versions have a common asymptotic slope, and bounding their intercepts gives the spectral constraint $b\le 4a(1-a)$. This yields the rectangular curve by tensor-spectrum duality. As an application, Zwick's algorithm for all-pairs shortest paths in directed unweighted graphs runs in $O(n^{2.5})$ time. Combining the rectangular bound with the $(\min,+)$-product improvement of Alman and Vassilevska Williams further gives $O(n^{2.4999})$ running time.

Thursday, October 08 2026, 00:00

Fast Almost-Uniform Sampling of Random $k$-SAT Solutions

Authors: Kun He, Zhidan Li, Kuan Yang

We study approximately uniform sampling of satisfying assignments from random $k$-SAT formulas. For every sufficiently large $k$ and density $0 < α\le 2^k/k^{16}$, we prove that, with high probability over the formula, there is a sampler whose output distribution is within total variation distance $\varepsilon$ of the uniform distribution on satisfying assignments and whose expected running time is at most $(nk(α+1)/\varepsilon)^C$, for a universal constant $C$. Our algorithm improves the counting and sampling algorithms obtained by Chen, Lonkar, Wang, Yang, and Yin (STOC 2025) at the density $2^k/\operatorname{poly}(k)$ with running time $(n/\varepsilon)^{\operatorname{poly}(k,α)}$. Our result achieves this density region for sampling with a polynomial degree independent of both the width and the density. Our algorithm separates a high-degree core from the remaining variables, and combines a recursive sampler for the residual formulas with approximate block heat-bath updates on the core. We adapt the recursive insertion-chain framework of Jain, Mizgerd, and Pham (2026) from $2$-trees to ordinary connected violation sets. Expansion and random literal signs yield uniform moment bounds for the resulting correlated lists across all residual formulas, allowing the signed-flow analysis to give a universal polynomial running-time degree. A polymer expansion and an exploration bound establish a polynomial spectral gap for the core dynamics.

Authors: Kun He, Zhidan Li, Kuan Yang

We study approximately uniform sampling of satisfying assignments from random $k$-SAT formulas. For every sufficiently large $k$ and density $0 < α\le 2^k/k^{16}$, we prove that, with high probability over the formula, there is a sampler whose output distribution is within total variation distance $\varepsilon$ of the uniform distribution on satisfying assignments and whose expected running time is at most $(nk(α+1)/\varepsilon)^C$, for a universal constant $C$. Our algorithm improves the counting and sampling algorithms obtained by Chen, Lonkar, Wang, Yang, and Yin (STOC 2025) at the density $2^k/\operatorname{poly}(k)$ with running time $(n/\varepsilon)^{\operatorname{poly}(k,α)}$. Our result achieves this density region for sampling with a polynomial degree independent of both the width and the density. Our algorithm separates a high-degree core from the remaining variables, and combines a recursive sampler for the residual formulas with approximate block heat-bath updates on the core. We adapt the recursive insertion-chain framework of Jain, Mizgerd, and Pham (2026) from $2$-trees to ordinary connected violation sets. Expansion and random literal signs yield uniform moment bounds for the resulting correlated lists across all residual formulas, allowing the signed-flow analysis to give a universal polynomial running-time degree. A polymer expansion and an exploration bound establish a polynomial spectral gap for the core dynamics.

Thursday, October 08 2026, 00:00

Subset Sum via Partial Match

Authors: Lixi Ye, Baitian Li

We show that the subset sum problem can be solved in time $O(2^{0.499999n})$, breaking the $2^{n/2}$ meet-in-the-middle barrier. Our approach builds on the representation technique framework of Randolph and Węgrzycki (STOC 2026). We choose a representation for which testing the compatibility of pairs of partial solution vectors is exactly the partial match problem. To beat exponent $1/2$ for subset sum, it then suffices to give a nontrivial partial match algorithm in a certain parameter regime. We achieve this by designing a depth-2 linear circuit for the partial match matrix, which yields an efficient algorithm via the framework of Alman and Li (FOCS 2025).

Authors: Lixi Ye, Baitian Li

We show that the subset sum problem can be solved in time $O(2^{0.499999n})$, breaking the $2^{n/2}$ meet-in-the-middle barrier. Our approach builds on the representation technique framework of Randolph and Węgrzycki (STOC 2026). We choose a representation for which testing the compatibility of pairs of partial solution vectors is exactly the partial match problem. To beat exponent $1/2$ for subset sum, it then suffices to give a nontrivial partial match algorithm in a certain parameter regime. We achieve this by designing a depth-2 linear circuit for the partial match matrix, which yields an efficient algorithm via the framework of Alman and Li (FOCS 2025).

Thursday, October 08 2026, 00:00

Color Coding for the Sherrington-Kirkpatrick Model

Authors: Alina Harbuzova, Saba Lepsveridze, Mahbod Majid, Ankur Moitra

We give a polynomial-time algorithm for approximating the partition function of mean-field mixed $p$-spin models to arbitrarily high accuracy throughout the second-moment regime. This improves the quasipolynomial-time algorithm of Bencs, Huang, Lee, Liu, and Regts (arXiv:2507.15616) and answers their open question. In particular, our result covers the entire replica-symmetric regime of the Sherrington--Kirkpatrick model. The algorithm is deterministic, runs in time polynomial in $n$ and $1/\varepsilon$, and succeeds for every typical realization of the disorder. Our main technical contribution is a new algorithmic application of color coding to the classical high-temperature expansion introduced by Aizenman, Lebowitz, and Ruelle in their study of fluctuations of the Sherrington--Kirkpatrick partition function. We combine this approach with the zero-freeness established by Bencs et al. (arXiv:2507.15616) to convert additive approximations into multiplicative ones.

Authors: Alina Harbuzova, Saba Lepsveridze, Mahbod Majid, Ankur Moitra

We give a polynomial-time algorithm for approximating the partition function of mean-field mixed $p$-spin models to arbitrarily high accuracy throughout the second-moment regime. This improves the quasipolynomial-time algorithm of Bencs, Huang, Lee, Liu, and Regts (arXiv:2507.15616) and answers their open question. In particular, our result covers the entire replica-symmetric regime of the Sherrington--Kirkpatrick model. The algorithm is deterministic, runs in time polynomial in $n$ and $1/\varepsilon$, and succeeds for every typical realization of the disorder. Our main technical contribution is a new algorithmic application of color coding to the classical high-temperature expansion introduced by Aizenman, Lebowitz, and Ruelle in their study of fluctuations of the Sherrington--Kirkpatrick partition function. We combine this approach with the zero-freeness established by Bencs et al. (arXiv:2507.15616) to convert additive approximations into multiplicative ones.

Thursday, October 08 2026, 00:00

Settling the Sample Complexity of Rényi Entropy Estimation

Authors: Qisheng Wang

Rényi entropy estimation has been comprehensively investigated by Acharya, Orlitsky, Suresh and Tyagi (SODA 2015; IEEE Trans. Inf. Theory 2017) and consequent works, whereas only the sample complexity of Rényi entropy estimation of integer order has been settled. In this paper, we settle the sample complexity of Rényi entropy estimation of noninteger order, thereby completing the complexity picture of Rényi entropy estimation. Specifically, we show that for any noninteger $α> 0$, it is sufficient and necessary to use \[ Θ\!\left(\frac{d^{\max\{1/α,1\}}}{\varepsilon^{1/α}\log(d)} + \frac{d^{|1-1/α|}}{\varepsilon^2}\right) \] samples to estimate the Rényi entropy of order $α$ of an unknown discrete distribution over an alphabet of size $d$ to within additive error $\varepsilon$. For the upper bound, we reduce the bias using a refined polynomial approximation estimator for large probabilities. For the lower bound, we employ a different hard instance equipped with a new moment matching construction. The constructive moment matching has constant bounded high-order moments, while attaining a fixed ratio between the $α$-th moments, which is of independent interest.

Authors: Qisheng Wang

Rényi entropy estimation has been comprehensively investigated by Acharya, Orlitsky, Suresh and Tyagi (SODA 2015; IEEE Trans. Inf. Theory 2017) and consequent works, whereas only the sample complexity of Rényi entropy estimation of integer order has been settled. In this paper, we settle the sample complexity of Rényi entropy estimation of noninteger order, thereby completing the complexity picture of Rényi entropy estimation. Specifically, we show that for any noninteger $α> 0$, it is sufficient and necessary to use \[ Θ\!\left(\frac{d^{\max\{1/α,1\}}}{\varepsilon^{1/α}\log(d)} + \frac{d^{|1-1/α|}}{\varepsilon^2}\right) \] samples to estimate the Rényi entropy of order $α$ of an unknown discrete distribution over an alphabet of size $d$ to within additive error $\varepsilon$. For the upper bound, we reduce the bias using a refined polynomial approximation estimator for large probabilities. For the lower bound, we employ a different hard instance equipped with a new moment matching construction. The constructive moment matching has constant bounded high-order moments, while attaining a fixed ratio between the $α$-th moments, which is of independent interest.

Thursday, October 08 2026, 00:00

Min-Plus Convolution Lower Bounds via a Higher-Order BSG Theorem

Authors: Nick Fischer, Ce Jin, Yinzhan Xu

Min-Plus Convolution is a central problem in fine-grained complexity, and the associated Min-Plus Convolution Hypothesis forms the basis for a wide range of conditional lower bounds for fundamental problems. It is closely connected to the APSP and 3SUM Hypotheses, and in fact implies both, making it a unifying hypothesis for two of the main pillars of the area. In this work we establish several strong results related to Min-Plus Convolution. We design a universe reduction, showing, under a plausible additive combinatorics assumption, that the Min-Plus Convolution Hypothesis is equivalent to the Strong Min-Plus Convolution Hypothesis. We also obtain tight conditional lower bounds for multiple long-standing problems, including Min-Max Convolution and Bounded Monotone Min-Plus Convolution. Our approach is inspired by Fischer's recent equivalence between several variants of APSP [STOC '26], but extending that technique to the arithmetic setting requires overcoming deep obstacles. To this end, we develop a novel additive structure theorem that can be viewed as a higher-order substitute of the Balog-Szemerédi-Gowers (BSG) theorem, allowing us to extract strong additive structure even from weakly structured sets. Building on this structural result, we show that certain structured 3SUM instances (namely, sets with low rank) can be solved in truly subquadratic time. This algorithm forms the main algorithmic ingredient in our reductions. Besides, it generalizes all previously known truly subquadratic-time special cases of 3SUM, and is therefore of independent interest.

Authors: Nick Fischer, Ce Jin, Yinzhan Xu

Min-Plus Convolution is a central problem in fine-grained complexity, and the associated Min-Plus Convolution Hypothesis forms the basis for a wide range of conditional lower bounds for fundamental problems. It is closely connected to the APSP and 3SUM Hypotheses, and in fact implies both, making it a unifying hypothesis for two of the main pillars of the area. In this work we establish several strong results related to Min-Plus Convolution. We design a universe reduction, showing, under a plausible additive combinatorics assumption, that the Min-Plus Convolution Hypothesis is equivalent to the Strong Min-Plus Convolution Hypothesis. We also obtain tight conditional lower bounds for multiple long-standing problems, including Min-Max Convolution and Bounded Monotone Min-Plus Convolution. Our approach is inspired by Fischer's recent equivalence between several variants of APSP [STOC '26], but extending that technique to the arithmetic setting requires overcoming deep obstacles. To this end, we develop a novel additive structure theorem that can be viewed as a higher-order substitute of the Balog-Szemerédi-Gowers (BSG) theorem, allowing us to extract strong additive structure even from weakly structured sets. Building on this structural result, we show that certain structured 3SUM instances (namely, sets with low rank) can be solved in truly subquadratic time. This algorithm forms the main algorithmic ingredient in our reductions. Besides, it generalizes all previously known truly subquadratic-time special cases of 3SUM, and is therefore of independent interest.

Thursday, October 08 2026, 00:00

Polynomial Kernels for Interval Completion

Authors: Zimo Sheng, Tian Bai, Mingyu xiao

An interval graph is the intersection graph of a family of intervals on the real line. \textsc{Interval Completion} asks whether a given graph can be transformed into an interval graph by adding at most $k$ edges. Although the problem is fixed-parameter tractable when parameterized by $k$, whether it admits a polynomial kernel has long been an open question. We resolve this question by giving the first polynomial kernel for \textsc{Interval Completion}. Our main contribution is a parameter-preserving polynomial-time reduction from \textsc{Interval Completion} to \textsc{Odd Cycle Transversal} (OCT). Combining this reduction with the known randomized and deterministic polynomial kernels for OCT and a polynomial-time reduction back to \textsc{Interval Completion}, we obtain a randomized kernel with $\widetilde O(k^{18})$ vertices and $\widetilde O(k^{36})$ edges, and a deterministic kernel with $O(k^{36})$ vertices and $O(k^{72})$ edges. Here, $\widetilde O$ suppresses polylogarithmic factors in $k$.

Authors: Zimo Sheng, Tian Bai, Mingyu xiao

An interval graph is the intersection graph of a family of intervals on the real line. \textsc{Interval Completion} asks whether a given graph can be transformed into an interval graph by adding at most $k$ edges. Although the problem is fixed-parameter tractable when parameterized by $k$, whether it admits a polynomial kernel has long been an open question. We resolve this question by giving the first polynomial kernel for \textsc{Interval Completion}. Our main contribution is a parameter-preserving polynomial-time reduction from \textsc{Interval Completion} to \textsc{Odd Cycle Transversal} (OCT). Combining this reduction with the known randomized and deterministic polynomial kernels for OCT and a polynomial-time reduction back to \textsc{Interval Completion}, we obtain a randomized kernel with $\widetilde O(k^{18})$ vertices and $\widetilde O(k^{36})$ edges, and a deterministic kernel with $O(k^{36})$ vertices and $O(k^{72})$ edges. Here, $\widetilde O$ suppresses polylogarithmic factors in $k$.

Thursday, October 08 2026, 00:00

On the Cyclic Assumption of the Cow-Path Search Algorithm

Authors: Yuan Ma, Yiqun Lisa Yin

In the cow-path problem, a cow must find a goal lying at an unknown distance on one of $w$ paths connected only at the origin, and performance is measured by competitive ratio. Kao, Reif and Tate designed an efficient randomized algorithm in which the cow visits the paths in a fixed cyclic order. They proved the algorithm is optimal for $w=2$, and subsequently Kao, Ma, Sipser and Yin proved its optimality for all $w$, with a claim that no algorithm does better than the best cyclic one. This note provides a detailed proof of that claim.

Authors: Yuan Ma, Yiqun Lisa Yin

In the cow-path problem, a cow must find a goal lying at an unknown distance on one of $w$ paths connected only at the origin, and performance is measured by competitive ratio. Kao, Reif and Tate designed an efficient randomized algorithm in which the cow visits the paths in a fixed cyclic order. They proved the algorithm is optimal for $w=2$, and subsequently Kao, Ma, Sipser and Yin proved its optimality for all $w$, with a claim that no algorithm does better than the best cyclic one. This note provides a detailed proof of that claim.

Thursday, October 08 2026, 00:00

3SUM Is Really Hard: A Real-to-Integer Reduction

Authors: Nick Fischer, Adam Polak, Jonas Schmidt

We show that if the 3SUM problem on integer-valued inputs can be solved in truly subquadratic time, then it can also be solved in truly subquadratic time on real-valued inputs. This answers an open problem posed by Chan, Vassilevska Williams, and Xu [STOC 2022], and constitutes the first such tight real-to-integer self-reduction in fine-grained complexity. Our proof relies on a surprising combination of the Frank--Tardos theorem from optimization with Freiman-type theorems from additive combinatorics.

Authors: Nick Fischer, Adam Polak, Jonas Schmidt

We show that if the 3SUM problem on integer-valued inputs can be solved in truly subquadratic time, then it can also be solved in truly subquadratic time on real-valued inputs. This answers an open problem posed by Chan, Vassilevska Williams, and Xu [STOC 2022], and constitutes the first such tight real-to-integer self-reduction in fine-grained complexity. Our proof relies on a surprising combination of the Frank--Tardos theorem from optimization with Freiman-type theorems from additive combinatorics.

Thursday, October 08 2026, 00:00

Attention via Black-Box Vector Search

Authors: Stepan Zharkov, Krish Singal, Ashwin Padaki, Alexandr Andoni

Sparse attention mechanisms estimate attention over $n$ tokens using a small subset of keys. Many existing approaches use maximum inner product search (MIPS) to retrieve the heaviest keys, which motivates the following question: given black-box access to a MIPS oracle, how many keys must be retrieved to output an $\varepsilon$-accurate attention estimate? We answer this question by unifying prior approaches through the framework of priority sampling. With a single MIPS index, we show that $Θ(\sqrt{n}/\varepsilon)$ retrieved keys are both sufficient and necessary. With $Θ(\log n)$ indices, we give an algorithm that retrieves only $O(\log n+1/\varepsilon^2)$ keys and prove that this is near-optimal. More generally, we design algorithms that establish a smooth tradeoff between the number of MIPS indices and number of retrieved keys. We then show that if we allow augmentation of keys and queries, we can bypass the above lower bounds: there exists a simple priority-sampling estimator using a single MIPS index and $O(1/\varepsilon^2)$ retrieved keys. When integrated into LLM inference, our algorithms outperform top-$k$ and sampling approaches used in prior work and yield attention approximation that scales favorably to long contexts.

Authors: Stepan Zharkov, Krish Singal, Ashwin Padaki, Alexandr Andoni

Sparse attention mechanisms estimate attention over $n$ tokens using a small subset of keys. Many existing approaches use maximum inner product search (MIPS) to retrieve the heaviest keys, which motivates the following question: given black-box access to a MIPS oracle, how many keys must be retrieved to output an $\varepsilon$-accurate attention estimate? We answer this question by unifying prior approaches through the framework of priority sampling. With a single MIPS index, we show that $Θ(\sqrt{n}/\varepsilon)$ retrieved keys are both sufficient and necessary. With $Θ(\log n)$ indices, we give an algorithm that retrieves only $O(\log n+1/\varepsilon^2)$ keys and prove that this is near-optimal. More generally, we design algorithms that establish a smooth tradeoff between the number of MIPS indices and number of retrieved keys. We then show that if we allow augmentation of keys and queries, we can bypass the above lower bounds: there exists a simple priority-sampling estimator using a single MIPS index and $O(1/\varepsilon^2)$ retrieved keys. When integrated into LLM inference, our algorithms outperform top-$k$ and sampling approaches used in prior work and yield attention approximation that scales favorably to long contexts.

Thursday, October 08 2026, 00:00

The Multiple Unicast Conjecture is False

Authors: Mark Braverman, Zhongtian He

The undirected multiple-unicast conjecture [LL04] asserts that network coding offers no throughput advantage over multicommodity flow. We refute this conjecture by constructing a deterministic linear network code over $\mathbb{F}_9$ on a 182-vertex bipartite subgraph of the point-line incidence graph of $\mathrm{PG}(2,9)$. The construction supports $157$ independent unicast sessions at common coding rate at least $1$, while every fractional multicommodity flow has common rate at most $147/157$. By the amplification theorem of~[BGS17], this yields a family of undirected multiple-unicast instances with coding gap $Ω((\log n)^\varepsilon)$ for some $\varepsilon>0$. We also introduce a nondeterministic model of network coding based on locally verifiable certificates, which guides our construction and may be of independent interest. Building on the high-girth graph and error-correcting code framework of [BH25], we use GPT-6 to find a nondeterministic counterexample based on a new choice of Reed--Solomon local codes, and then convert this example into a causal code using an edge orientation and local search.

Authors: Mark Braverman, Zhongtian He

The undirected multiple-unicast conjecture [LL04] asserts that network coding offers no throughput advantage over multicommodity flow. We refute this conjecture by constructing a deterministic linear network code over $\mathbb{F}_9$ on a 182-vertex bipartite subgraph of the point-line incidence graph of $\mathrm{PG}(2,9)$. The construction supports $157$ independent unicast sessions at common coding rate at least $1$, while every fractional multicommodity flow has common rate at most $147/157$. By the amplification theorem of~[BGS17], this yields a family of undirected multiple-unicast instances with coding gap $Ω((\log n)^\varepsilon)$ for some $\varepsilon>0$. We also introduce a nondeterministic model of network coding based on locally verifiable certificates, which guides our construction and may be of independent interest. Building on the high-girth graph and error-correcting code framework of [BH25], we use GPT-6 to find a nondeterministic counterexample based on a new choice of Reed--Solomon local codes, and then convert this example into a causal code using an edge orientation and local search.

Thursday, October 08 2026, 00:00

BetweenCut: Private Heavy-Node Classification with Doubly Logarithmic Error in Tree Height

Authors: Ergute Bao, Graham Cormode, Xiaokui Xiao, Ting Yu

Finding heavy nodes in a tree---those whose counts exceed a given threshold---is a building block for analysis and learning over structured data. Achieving record-level differential privacy (DP) without sacrificing accuracy is challenging because each record contributes to counts along an entire root-to-leaf path, allowing privacy costs to accumulate across levels. Existing methods account for the multiple threshold comparisons for each record incur additive error margins of $Ω_{\varepsilon,δ}(\log h)$ or $Ω_{\varepsilon,δ}(\sqrt{\log h})$ for tree height $h$. We introduce \textsc{BetweenCut}, an $(\varepsilon,δ)$-DP algorithm with an additive error margin of $O_{\varepsilon,δ}(\log\log h)$, improving the existing bounds for deep trees. This error holds simultaneously for all nodes and is independent of the input database size.

Authors: Ergute Bao, Graham Cormode, Xiaokui Xiao, Ting Yu

Finding heavy nodes in a tree---those whose counts exceed a given threshold---is a building block for analysis and learning over structured data. Achieving record-level differential privacy (DP) without sacrificing accuracy is challenging because each record contributes to counts along an entire root-to-leaf path, allowing privacy costs to accumulate across levels. Existing methods account for the multiple threshold comparisons for each record incur additive error margins of $Ω_{\varepsilon,δ}(\log h)$ or $Ω_{\varepsilon,δ}(\sqrt{\log h})$ for tree height $h$. We introduce \textsc{BetweenCut}, an $(\varepsilon,δ)$-DP algorithm with an additive error margin of $O_{\varepsilon,δ}(\log\log h)$, improving the existing bounds for deep trees. This error holds simultaneously for all nodes and is independent of the input database size.

Thursday, October 08 2026, 00:00

Breaking the $\sqrt{3}$ Barrier for Maximum Weighted $3$-Set Packing

Authors: Weitian Tong, Yao Xu

We give a deterministic polynomial-time $1.6908$-approximation for Maximum Weighted $3$-Set Packing, breaking the $\sqrt3$ locality-gap barrier of squared-weight local search. The approximation ratio for this problem progressed from Berman's $2$ [Ber00] to Neuwohner's $2-\frac{1}{63{,}700{,}992}+ε$ [Neu21]. Thiery and Ward then obtained $1.786$ [TW23], while Thiery subsequently improved the bound to $1.761+ε$ and finally to $\sqrt3 \approx 1.732051$ through a layered exchange analysis [Thi23]. Thiery also proved that $\sqrt3$ is a locality-gap lower bound for the squared-weight objective even with exchanges of arbitrary size. Our algorithm performs in two phases and combines two objectives. Phase~I computes a bounded-exchange local optimum for the squared-weight potential and analyzes it through Thiery's layered framework, while strengthening the terminal analysis by preserving internal tree-edge slack for nonsingleton components and exploiting the incidence structure of $3$-sets for final singletons. This yields an augmented structural inequality with residual positive claw gain under the original objective. Phase~II switches to the original objective and recovers sufficient residual gain through an auxiliary weighted $9$-Set Packing instance. A covering argument transfers the structural bound through the high-girth lift used only in the analysis.

Authors: Weitian Tong, Yao Xu

We give a deterministic polynomial-time $1.6908$-approximation for Maximum Weighted $3$-Set Packing, breaking the $\sqrt3$ locality-gap barrier of squared-weight local search. The approximation ratio for this problem progressed from Berman's $2$ [Ber00] to Neuwohner's $2-\frac{1}{63{,}700{,}992}+ε$ [Neu21]. Thiery and Ward then obtained $1.786$ [TW23], while Thiery subsequently improved the bound to $1.761+ε$ and finally to $\sqrt3 \approx 1.732051$ through a layered exchange analysis [Thi23]. Thiery also proved that $\sqrt3$ is a locality-gap lower bound for the squared-weight objective even with exchanges of arbitrary size. Our algorithm performs in two phases and combines two objectives. Phase~I computes a bounded-exchange local optimum for the squared-weight potential and analyzes it through Thiery's layered framework, while strengthening the terminal analysis by preserving internal tree-edge slack for nonsingleton components and exploiting the incidence structure of $3$-sets for final singletons. This yields an augmented structural inequality with residual positive claw gain under the original objective. Phase~II switches to the original objective and recovers sufficient residual gain through an auxiliary weighted $9$-Set Packing instance. A covering argument transfers the structural bound through the high-girth lift used only in the analysis.

Thursday, October 08 2026, 00:00

A deterministic algorithm for signing bipartite graphs at the Ramanujan bound

Authors: Zhiqiang Xu

We give a deterministic polynomial-time algorithm for the Bilu--Linial signing problem on bipartite graphs. For every finite simple bipartite graph of maximum degree at most an integer $Δ\ge3$, the algorithm assigns signs to its edges so that the signed adjacency matrix has operator norm strictly less than $2\sqrt{Δ-1}$. Our algorithm builds on the randomized recursive repair framework of Jadbabaie, Saberi, and Sra~\cite{JSS26}, with deterministic rules for sign selection and vertex deletion.

Authors: Zhiqiang Xu

We give a deterministic polynomial-time algorithm for the Bilu--Linial signing problem on bipartite graphs. For every finite simple bipartite graph of maximum degree at most an integer $Δ\ge3$, the algorithm assigns signs to its edges so that the signed adjacency matrix has operator norm strictly less than $2\sqrt{Δ-1}$. Our algorithm builds on the randomized recursive repair framework of Jadbabaie, Saberi, and Sra~\cite{JSS26}, with deterministic rules for sign selection and vertex deletion.

Thursday, October 08 2026, 00:00

An $n^{0.3+\varepsilon}$-Approximation for Steiner $k$-Forest

Authors: Eden Chlamtáč

We give an $n^{0.3+\varepsilon}$-approximation algorithm for the Steiner $k$-Forest problem, for any constant $\varepsilon>0$. As a function of $n$, this improves over the $O(\min\{\sqrt{n},\sqrt{k}\})$-approximation of Gupta et al. [ESA'07, TALG'10] which has stood for nearly two decades for the general case, as well as the later $n^{0.448}$-approximation of Dinitz et. al [APPROX-RANDOM'14, TALG'17] for the uniform weight case. On the other hand, we show that, due to lower bounds on the Densest $k$-Subgraph problem, the $O(\sqrt k)$-approximation for Steiner $k$-Forest likely cannot be improved. Specifically, we show that for any sufficiently small $\varepsilon>0$, an $O(k^{1/2-\varepsilon})$-approximation for Steiner $k$-Forest would surpass known degree-$n^{Ω(\varepsilon^2)}$ Sum-of-Squares integrality gaps for Densest k-Subgraph and refute the corresponding dense-versus-random conjecture.

Authors: Eden Chlamtáč

We give an $n^{0.3+\varepsilon}$-approximation algorithm for the Steiner $k$-Forest problem, for any constant $\varepsilon>0$. As a function of $n$, this improves over the $O(\min\{\sqrt{n},\sqrt{k}\})$-approximation of Gupta et al. [ESA'07, TALG'10] which has stood for nearly two decades for the general case, as well as the later $n^{0.448}$-approximation of Dinitz et. al [APPROX-RANDOM'14, TALG'17] for the uniform weight case. On the other hand, we show that, due to lower bounds on the Densest $k$-Subgraph problem, the $O(\sqrt k)$-approximation for Steiner $k$-Forest likely cannot be improved. Specifically, we show that for any sufficiently small $\varepsilon>0$, an $O(k^{1/2-\varepsilon})$-approximation for Steiner $k$-Forest would surpass known degree-$n^{Ω(\varepsilon^2)}$ Sum-of-Squares integrality gaps for Densest k-Subgraph and refute the corresponding dense-versus-random conjecture.

Thursday, October 08 2026, 00:00

Simulated annealing and Weak Poincaré inequalities with inverse-polynomial accuracy for the Sherrington-Kirkpatrick model

Authors: Zhe Hou, Jingcheng Liu, Yixiao Yu

We study sampling from the Gibbs distribution of the Sherrington-Kirkpatrick (SK) model with Glauber dynamics. For every fixed inverse temperature $0\leqβ<1$ and every fixed $M,D>0$, we give a polynomial-time simulated annealing algorithm whose output distribution is within $n^{-M}$ total-variation distance of the Gibbs distribution, with probability at least $1-n^{-D}$ over the interaction matrix. The algorithm starts from uniform product spins and uses Glauber dynamics along an increasing inverse-temperature schedule. The same approach also yields partition-function estimates with relative error $n^{-M}$. The key ingredient is a quantitative weak Poincaré inequality. Building on the stochastic-localization approach to weak Poincaré inequalities [Davies, Lee, Sandhu, and Shi, arXiv:2607.08160, 2026], we use Gaussian isoperimetry to directly compare exact stochastic localization paths. Our comparison tolerates failures of local Lipschitz continuity of the posterior mean by controlling their accumulated cost. The local Lipschitzness comes from approximating the posterior means by stationary points of the Thouless-Anderson-Palmer (TAP) free energy in locally strongly convex regions located by approximate message passing, a paradigm introduced by algorithmic stochastic localization [El Alaoui, Montanari, and Sellke, 2025; Celentano, 2024]. The approximation errors are roughly characterized by the validity of the TAP gradient equations, but in a different coordinate. To show that the errors rarely accumulate too much, we need a strong concentration control. A direct argument would require solving a variant of an open problem by Talagrand [2010, Research Problem 1.7.9]. We bypass this open problem with an intermediate conditioning step and transfer the control back by establishing the stability of the TAP gradient under deletion of coordinates.

Authors: Zhe Hou, Jingcheng Liu, Yixiao Yu

We study sampling from the Gibbs distribution of the Sherrington-Kirkpatrick (SK) model with Glauber dynamics. For every fixed inverse temperature $0\leqβ<1$ and every fixed $M,D>0$, we give a polynomial-time simulated annealing algorithm whose output distribution is within $n^{-M}$ total-variation distance of the Gibbs distribution, with probability at least $1-n^{-D}$ over the interaction matrix. The algorithm starts from uniform product spins and uses Glauber dynamics along an increasing inverse-temperature schedule. The same approach also yields partition-function estimates with relative error $n^{-M}$. The key ingredient is a quantitative weak Poincaré inequality. Building on the stochastic-localization approach to weak Poincaré inequalities [Davies, Lee, Sandhu, and Shi, arXiv:2607.08160, 2026], we use Gaussian isoperimetry to directly compare exact stochastic localization paths. Our comparison tolerates failures of local Lipschitz continuity of the posterior mean by controlling their accumulated cost. The local Lipschitzness comes from approximating the posterior means by stationary points of the Thouless-Anderson-Palmer (TAP) free energy in locally strongly convex regions located by approximate message passing, a paradigm introduced by algorithmic stochastic localization [El Alaoui, Montanari, and Sellke, 2025; Celentano, 2024]. The approximation errors are roughly characterized by the validity of the TAP gradient equations, but in a different coordinate. To show that the errors rarely accumulate too much, we need a strong concentration control. A direct argument would require solving a variant of an open problem by Talagrand [2010, Research Problem 1.7.9]. We bypass this open problem with an intermediate conditioning step and transfer the control back by establishing the stability of the TAP gradient under deletion of coordinates.

Thursday, October 08 2026, 00:00

Packing Diverse Shortest Cycles

Authors: Akanksha Agrawal, Fedor V. Fomin, Petr A. Golovach, Vinod Gupta, Yash Hiren More, Vidya Sagar Sharma

Bentert, Fomin, Golovach, Korhonen, Lochet, Panolan, Ramanujan, Saurabh, and Simonov (SODA 2025) initiated the parameterized study of Edge-Disjoint Shortest Cycle Packing: given a weighted graph $G$ and an integer $k$, decide whether $G$ contains $k$ edge-disjoint cycles of minimum weight. They showed that the problem admits an algorithm running in time $n^{O(k^6)}$ and asked whether it is fixed-parameter tractable or $W[1]$-hard parameterized by $k$. We resolve this question by proving that Edge-Disjoint Shortest Cycle Packing is $W[1]$-hard parameterized by $k$, even on unweighted subcubic graphs. The same lower bound also applies to the vertex-disjoint variant. For planar graphs, they provides a construction of a kernel with $O(k^2)$ vertices and an algorithm running in time $k^{O(k)} \cdot n^{O(1)}$, and explicitly asked whether the problem admits a single-exponential algorithm of running time $2^{O(k)} \cdot n^{O(1)}$. Rather than addressing this question in isolation, we introduce a more general framework, Diverse Shortest Cycle Coverage, which asks for $k$ shortest cycles that may overlap in a controlled way while maximizing the total weight of covered edges. This framework simultaneously captures edge-disjoint shortest cycle packing, the problem of finding diverse shortest cycles, and the problem of maximizing edge coverage by shortest cycles. Our main algorithmic result shows that Diverse Shortest Cycle Coverage can be solved on planar graphs in time $2^{O(k)} \cdot n^{O(1)}$, thereby giving a single-exponential algorithm for Edge-Disjoint Shortest Cycle Packing as a special case. The key idea of our algorithm is a structural analysis of the Laminar Shortest Cycles Tree, a tree-like decomposition that reveals a laminar interaction pattern among shortest cycles in planar graphs and enables an efficient dynamic programming algorithm.

Authors: Akanksha Agrawal, Fedor V. Fomin, Petr A. Golovach, Vinod Gupta, Yash Hiren More, Vidya Sagar Sharma

Bentert, Fomin, Golovach, Korhonen, Lochet, Panolan, Ramanujan, Saurabh, and Simonov (SODA 2025) initiated the parameterized study of Edge-Disjoint Shortest Cycle Packing: given a weighted graph $G$ and an integer $k$, decide whether $G$ contains $k$ edge-disjoint cycles of minimum weight. They showed that the problem admits an algorithm running in time $n^{O(k^6)}$ and asked whether it is fixed-parameter tractable or $W[1]$-hard parameterized by $k$. We resolve this question by proving that Edge-Disjoint Shortest Cycle Packing is $W[1]$-hard parameterized by $k$, even on unweighted subcubic graphs. The same lower bound also applies to the vertex-disjoint variant. For planar graphs, they provides a construction of a kernel with $O(k^2)$ vertices and an algorithm running in time $k^{O(k)} \cdot n^{O(1)}$, and explicitly asked whether the problem admits a single-exponential algorithm of running time $2^{O(k)} \cdot n^{O(1)}$. Rather than addressing this question in isolation, we introduce a more general framework, Diverse Shortest Cycle Coverage, which asks for $k$ shortest cycles that may overlap in a controlled way while maximizing the total weight of covered edges. This framework simultaneously captures edge-disjoint shortest cycle packing, the problem of finding diverse shortest cycles, and the problem of maximizing edge coverage by shortest cycles. Our main algorithmic result shows that Diverse Shortest Cycle Coverage can be solved on planar graphs in time $2^{O(k)} \cdot n^{O(1)}$, thereby giving a single-exponential algorithm for Edge-Disjoint Shortest Cycle Packing as a special case. The key idea of our algorithm is a structural analysis of the Laminar Shortest Cycles Tree, a tree-like decomposition that reveals a laminar interaction pattern among shortest cycles in planar graphs and enables an efficient dynamic programming algorithm.

Thursday, October 08 2026, 00:00

Envy-free Allocations with Individual Payments

Authors: Robert Bredereck, Eva Deltl, Tanmay Inamdar, Pallavi Jain, Pranjal Pandey

When an envy-free allocation of indivisible goods does not exist, monetary transfers can restore envy-freeness. Existing work on fair division with subsidies, however, typically assumes that these payments are provided by an external source, an assumption that may be unrealistic in many applications. We address this limitation by allowing only monetary transfers between agents, with each agent's payments constrained by their individual budget. We show that while it is polynomial-time tractable to determine whether a given allocation can be made envy-free by payments under individual budgets, the general problem of computing such an allocation from scratch is NP-hard, even when agents have relatively large budgets. Motivated by this intractability, we conduct a parameterized complexity analysis, establishing fixed-parameter tractability with respect to the number of goods or to the joint parameter number of agents and good types, and we provide efficient algorithms in several special cases. For explicitly listed items, our type-based algorithm answers the envy-freeness part of an open question of T. T. Nguyen and J. Rothe, "Complexity Results and Exact Algorithms for Fair Division of Indivisible Items: A Survey."

Authors: Robert Bredereck, Eva Deltl, Tanmay Inamdar, Pallavi Jain, Pranjal Pandey

When an envy-free allocation of indivisible goods does not exist, monetary transfers can restore envy-freeness. Existing work on fair division with subsidies, however, typically assumes that these payments are provided by an external source, an assumption that may be unrealistic in many applications. We address this limitation by allowing only monetary transfers between agents, with each agent's payments constrained by their individual budget. We show that while it is polynomial-time tractable to determine whether a given allocation can be made envy-free by payments under individual budgets, the general problem of computing such an allocation from scratch is NP-hard, even when agents have relatively large budgets. Motivated by this intractability, we conduct a parameterized complexity analysis, establishing fixed-parameter tractability with respect to the number of goods or to the joint parameter number of agents and good types, and we provide efficient algorithms in several special cases. For explicitly listed items, our type-based algorithm answers the envy-freeness part of an open question of T. T. Nguyen and J. Rothe, "Complexity Results and Exact Algorithms for Fair Division of Indivisible Items: A Survey."

Thursday, October 08 2026, 00:00

Generating cyclic pivot Gray codes for well-ordered $k$-degenerate graphs in constant amortized time

Authors: Lei Dong, Dennis Wong, Bowie Liu, Rui Bao, Lin Chen, Chan-Tong Lam, Sio-Kei Im

A graph $G$ is $k$-degenerate if there exists an ordering $v_1, v_2, \dots, v_n$ of its vertices such that each vertex $v_i$ has at most $k$ neighbors $v_j$ in $G$ with $j < i$. A well-ordered $k$-degenerate graph is a labeled graph on the vertex set $\{1, 2, \dots, n\}$ in which every vertex $i$ has at most $k$ neighbors among $1, 2, \dots, i-1$. We present the first simple algorithms that generate, rank, and unrank cyclic pivot Gray codes for well-ordered $k$-degenerate graphs, where consecutive graphs differ by the addition, removal, or pivoting of a single edge. Our algorithm generates each well-ordered $k$-degenerate graph in constant amortized time per graph, using $O(n^2)$ space, while ranking and unranking take $O(n^2)$ time and $O(n^2)$ space.

Authors: Lei Dong, Dennis Wong, Bowie Liu, Rui Bao, Lin Chen, Chan-Tong Lam, Sio-Kei Im

A graph $G$ is $k$-degenerate if there exists an ordering $v_1, v_2, \dots, v_n$ of its vertices such that each vertex $v_i$ has at most $k$ neighbors $v_j$ in $G$ with $j < i$. A well-ordered $k$-degenerate graph is a labeled graph on the vertex set $\{1, 2, \dots, n\}$ in which every vertex $i$ has at most $k$ neighbors among $1, 2, \dots, i-1$. We present the first simple algorithms that generate, rank, and unrank cyclic pivot Gray codes for well-ordered $k$-degenerate graphs, where consecutive graphs differ by the addition, removal, or pivoting of a single edge. Our algorithm generates each well-ordered $k$-degenerate graph in constant amortized time per graph, using $O(n^2)$ space, while ranking and unranking take $O(n^2)$ time and $O(n^2)$ space.

Thursday, October 08 2026, 00:00

Fine-Grained Hardness of Approximating Dynamic Time Warping

Authors: Jihan Wang

We prove conditional lower bounds for approximating dynamic time warping (DTW) over the uniform metric on three symbols. Let $N, M$ be the two string lengths and $n, m$ their respective numbers of runs. Under the Gap Block Disjointness (GBD) hypothesis, for every fixed $κ\in (0,1/6)$ and $δ\in (0,1)$, no deterministic algorithm $N^{κδ}$-approximates DTW on two explicit strings of length $N$ in $O(N^{2-δ})$ time. This matches the known tradeoff between approximation and running-time exponents for deterministic algorithms within any fixed factor greater than six in the approximation exponent. For run-length encoded strings, the Orthogonal Vectors Hypothesis (OVH) rules out any constant-factor approximation in $\widetilde{O}((nm)^{1-δ})$ time for every constant $δ>0$. More generally, for every fixed $η\in (0,1)$, it rules out $(N+M)^{1-η}$-approximation in the same running time. These bounds extend to every fixed metric with at least three points, including absolute distance on $\{0,1,2\}$. Both reductions use long runs to force equal-symbol matches in low-cost alignments. For explicit strings, we combine Boolean gadgets with deterministic gap amplification to obtain a polynomial approximation gap. For run-length encoded strings, an encoding of regular-expression membership gives accepting instances an alignment whose cost does not increase as selected runs grow. Rejecting instances have distance at least the chosen run length, while the number of runs stays fixed.

Authors: Jihan Wang

We prove conditional lower bounds for approximating dynamic time warping (DTW) over the uniform metric on three symbols. Let $N, M$ be the two string lengths and $n, m$ their respective numbers of runs. Under the Gap Block Disjointness (GBD) hypothesis, for every fixed $κ\in (0,1/6)$ and $δ\in (0,1)$, no deterministic algorithm $N^{κδ}$-approximates DTW on two explicit strings of length $N$ in $O(N^{2-δ})$ time. This matches the known tradeoff between approximation and running-time exponents for deterministic algorithms within any fixed factor greater than six in the approximation exponent. For run-length encoded strings, the Orthogonal Vectors Hypothesis (OVH) rules out any constant-factor approximation in $\widetilde{O}((nm)^{1-δ})$ time for every constant $δ>0$. More generally, for every fixed $η\in (0,1)$, it rules out $(N+M)^{1-η}$-approximation in the same running time. These bounds extend to every fixed metric with at least three points, including absolute distance on $\{0,1,2\}$. Both reductions use long runs to force equal-symbol matches in low-cost alignments. For explicit strings, we combine Boolean gadgets with deterministic gap amplification to obtain a polynomial approximation gap. For run-length encoded strings, an encoding of regular-expression membership gives accepting instances an alignment whose cost does not increase as selected runs grow. Rejecting instances have distance at least the chosen run length, while the number of runs stays fixed.

Thursday, October 08 2026, 00:00

Lower Bounds for Parallel Diffusion Sampling

Authors: Yiwen Kou, Yimeng Wang

Standard diffusion samplers generate samples through repeated evaluations of a learned score function. Parallel sampling methods seek to accelerate generation by trading additional evaluations for fewer sequential rounds. This raises the question of how much sequential dependence is unavoidable, even when many score queries can be made simultaneously. We establish the first polynomial parallel-round lower bounds for diffusion sampling with approximate scores. Specifically, we prove (1) a $\widetildeΩ(d^{1/3})$-round lower bound for sampling smooth, near-isotropic Gaussian mixtures in $R^d$, and (2) an $Ω(d)$-round lower bound for uniform sampling from anisotropic axis-aligned boxes contained in the unit ball. Both bounds hold for arbitrary randomized algorithms making polynomially many queries per round at arbitrary locations and noise levels, with inverse-polynomial score error and constant total variation accuracy. The linear bound is tight for our box family. Our constructions use fixed approximate score oracles that enforce sequential access to hidden information while satisfying the accuracy guarantee at every noise level.

Authors: Yiwen Kou, Yimeng Wang

Standard diffusion samplers generate samples through repeated evaluations of a learned score function. Parallel sampling methods seek to accelerate generation by trading additional evaluations for fewer sequential rounds. This raises the question of how much sequential dependence is unavoidable, even when many score queries can be made simultaneously. We establish the first polynomial parallel-round lower bounds for diffusion sampling with approximate scores. Specifically, we prove (1) a $\widetildeΩ(d^{1/3})$-round lower bound for sampling smooth, near-isotropic Gaussian mixtures in $R^d$, and (2) an $Ω(d)$-round lower bound for uniform sampling from anisotropic axis-aligned boxes contained in the unit ball. Both bounds hold for arbitrary randomized algorithms making polynomially many queries per round at arbitrary locations and noise levels, with inverse-polynomial score error and constant total variation accuracy. The linear bound is tight for our box family. Our constructions use fixed approximate score oracles that enforce sequential access to hidden information while satisfying the accuracy guarantee at every noise level.

Thursday, October 08 2026, 00:00

Massively Parallel Algorithms for Huffman Coding

Authors: Masoud Seddighin, Saeed Seddighin

Huffman coding is one of the oldest and most fundamental problems in computer science. Given a string of length $\TextLength$ over a general alphabet, the goal is to assign a binary codeword to each character so that no codeword is a prefix of another and the total encoded length of the string is minimized. Huffman coding is widely used in practical compression systems, including file compression. As modern datasets continue to grow, it is natural to study whether a Huffman code can be constructed efficiently in the massively parallel computation (\MPC) model. The celebrated Huffman coding algorithm admits two straightforward \MPC implementations: for any constant $ε\in(0,1)$, one uses $O(\TextLength^ε)$ memory per machine but requires $Θ(\log \TextLength)$ rounds, while the other runs in $O(1)$ rounds but requires $Θ(\sqrt{\TextLength})$ memory per machine. We give the first nontrivial \MPC algorithm for Huffman coding that bypasses both limitations. For every constant $ε>0$, our algorithm uses $O_ε(\log\log \TextLength)$ rounds and $\softO(\TextLength^ε)$ memory per machine, while its total memory and total computation are $\softO(\TextLength)$. This provides a rare example in which an exact solution to a problem whose classical algorithm is sequential in nature can be obtained in a sublogarithmic number of \MPC rounds.

Authors: Masoud Seddighin, Saeed Seddighin

Huffman coding is one of the oldest and most fundamental problems in computer science. Given a string of length $\TextLength$ over a general alphabet, the goal is to assign a binary codeword to each character so that no codeword is a prefix of another and the total encoded length of the string is minimized. Huffman coding is widely used in practical compression systems, including file compression. As modern datasets continue to grow, it is natural to study whether a Huffman code can be constructed efficiently in the massively parallel computation (\MPC) model. The celebrated Huffman coding algorithm admits two straightforward \MPC implementations: for any constant $ε\in(0,1)$, one uses $O(\TextLength^ε)$ memory per machine but requires $Θ(\log \TextLength)$ rounds, while the other runs in $O(1)$ rounds but requires $Θ(\sqrt{\TextLength})$ memory per machine. We give the first nontrivial \MPC algorithm for Huffman coding that bypasses both limitations. For every constant $ε>0$, our algorithm uses $O_ε(\log\log \TextLength)$ rounds and $\softO(\TextLength^ε)$ memory per machine, while its total memory and total computation are $\softO(\TextLength)$. This provides a rare example in which an exact solution to a problem whose classical algorithm is sequential in nature can be obtained in a sublogarithmic number of \MPC rounds.

Thursday, October 08 2026, 00:00

On the complexity of the single-move labeled token routing problem

Authors: Nicolas Bousquet, Remy El Sabeh, Amer E. Mouawad, Naomi Nishimura

In neutral-atom quantum computers, atoms are moved to target positions along paths of empty positions, and a target position may be reserved for one species of atom. Motivated by this task, we introduce Single-Move Labeled Token Routing: every source and every target vertex of a graph is assigned a set of labels, and tokens occupy the sources. A solution consists of a matching that assigns each source to a compatible target (one whose label set intersects its own), a route for each matched pair, and a movement order in which, when a token is moved, its route contains no other token. The problem is known to be polynomial-time solvable when every source is compatible with every target, and $\mathsf{NP}$-complete on grid graphs when each source is compatible with exactly one target. We prove that the latter case remains $\mathsf{NP}$-complete on grids and on planar graphs of maximum degree four even when some solution has pairwise edge-disjoint routes. On trees, the problem is known to be $\mathsf{NP}$-complete even for maximum degree three. We study trees through the solution edge multiplicity, the largest number of routes of a solution sharing an edge, and the candidate edge multiplicity, the largest number of compatible pairs whose paths share an edge. We prove that on trees of maximum degree three, the problem is $\mathsf{W}[1]$-hard parameterized by a bound on the solution edge multiplicity, even when a movement order is given, and that on trees of unbounded degree, it is $\mathsf{NP}$-complete even when the candidate edge multiplicity is at most eight. We show that on trees the problem is fixed-parameter tractable parameterized by the maximum degree together with the candidate edge multiplicity, and also by the candidate vertex multiplicity, the same count at vertices. Unless $\mathsf{P}=\mathsf{NP}$, neither the maximum degree nor the candidate edge multiplicity can be omitted.

Authors: Nicolas Bousquet, Remy El Sabeh, Amer E. Mouawad, Naomi Nishimura

In neutral-atom quantum computers, atoms are moved to target positions along paths of empty positions, and a target position may be reserved for one species of atom. Motivated by this task, we introduce Single-Move Labeled Token Routing: every source and every target vertex of a graph is assigned a set of labels, and tokens occupy the sources. A solution consists of a matching that assigns each source to a compatible target (one whose label set intersects its own), a route for each matched pair, and a movement order in which, when a token is moved, its route contains no other token. The problem is known to be polynomial-time solvable when every source is compatible with every target, and $\mathsf{NP}$-complete on grid graphs when each source is compatible with exactly one target. We prove that the latter case remains $\mathsf{NP}$-complete on grids and on planar graphs of maximum degree four even when some solution has pairwise edge-disjoint routes. On trees, the problem is known to be $\mathsf{NP}$-complete even for maximum degree three. We study trees through the solution edge multiplicity, the largest number of routes of a solution sharing an edge, and the candidate edge multiplicity, the largest number of compatible pairs whose paths share an edge. We prove that on trees of maximum degree three, the problem is $\mathsf{W}[1]$-hard parameterized by a bound on the solution edge multiplicity, even when a movement order is given, and that on trees of unbounded degree, it is $\mathsf{NP}$-complete even when the candidate edge multiplicity is at most eight. We show that on trees the problem is fixed-parameter tractable parameterized by the maximum degree together with the candidate edge multiplicity, and also by the candidate vertex multiplicity, the same count at vertices. Unless $\mathsf{P}=\mathsf{NP}$, neither the maximum degree nor the candidate edge multiplicity can be omitted.

Thursday, October 08 2026, 00:00

Efficient Algorithms for Online Subadditive Combinatorial Allocations

Authors: Calum MacRury, Rian Neogi, Kanstantsin Pashkovich, Sahil Singla, Siddarth M Sundaram, Chaitanya Swamy

For the online combinatorial allocation problem with subadditive valuations, Correa and Cristi (STOC 2023) proved the existence of a $6$-competitive online algorithm, improving on the previous best $O(\log\!\log m)$-competitive online algorithm due to Dütting, Kesselheim, and Lucier (FOCS 2020), where $m$ is the number of items. However, Correa and Cristi's result is existential, and it was left open whether a constant competitive ratio is attainable via an efficient online algorithm that uses a polynomial number of demand oracle queries. In this work, we answer this affirmatively, giving an expected-polynomial-time $(6 + ε)$-competitive online algorithm for any constant $ε> 0$. Our techniques also recover, in the offline setting, the $(2 + ε)$-approximation result of Feige (STOC, 2006). Finally, when the buyers' valuations are drawn from identical distributions, we exploit symmetry to obtain an improved $(60/11+ε)$-competitive algorithm. Starting with the natural configuration LP relaxation for the problem, our main technical contribution is a recursive Bundle Score Generator (BSG) that resolves item conflicts by assigning correlated scores to the items requested by each buyer. Unlike the Random Score Generator whose existence is shown by Correa and Cristi, our BSG is efficiently computable in expected polynomial time. Moreover, it satisfies a stochastic dominance property that is sufficient to recover both Feige's offline result and Correa and Cristi's online result.

Authors: Calum MacRury, Rian Neogi, Kanstantsin Pashkovich, Sahil Singla, Siddarth M Sundaram, Chaitanya Swamy

For the online combinatorial allocation problem with subadditive valuations, Correa and Cristi (STOC 2023) proved the existence of a $6$-competitive online algorithm, improving on the previous best $O(\log\!\log m)$-competitive online algorithm due to Dütting, Kesselheim, and Lucier (FOCS 2020), where $m$ is the number of items. However, Correa and Cristi's result is existential, and it was left open whether a constant competitive ratio is attainable via an efficient online algorithm that uses a polynomial number of demand oracle queries. In this work, we answer this affirmatively, giving an expected-polynomial-time $(6 + ε)$-competitive online algorithm for any constant $ε> 0$. Our techniques also recover, in the offline setting, the $(2 + ε)$-approximation result of Feige (STOC, 2006). Finally, when the buyers' valuations are drawn from identical distributions, we exploit symmetry to obtain an improved $(60/11+ε)$-competitive algorithm. Starting with the natural configuration LP relaxation for the problem, our main technical contribution is a recursive Bundle Score Generator (BSG) that resolves item conflicts by assigning correlated scores to the items requested by each buyer. Unlike the Random Score Generator whose existence is shown by Correa and Cristi, our BSG is efficiently computable in expected polynomial time. Moreover, it satisfies a stochastic dominance property that is sufficient to recover both Feige's offline result and Correa and Cristi's online result.

Thursday, October 08 2026, 00:00

Analysis of the two-for-one swap heuristic for approximating the maximum independent set in a k-polymatroid

Authors: Adrian Calinescu, Gruia Calinescu

Let f:2^N --> \cZ^+ be a polymatroid (an integer-valued non-decreasing submodular set function with f(emptyset) = 0). A k-polymatroid satisfies that f(e) <= k for all e in N. We call a subset S of N independent if f(S) equals the sum of f(e) over the elements e of S and f(e) > 0 for all e in S. Finding a maximum-size independent set in a 2-polymatroid has been studied and polynomial-time algorithms are known for linear polymatroids. For k >= 3, the problem is NP-hard, and an approximation algorithm with ratio approaching 2/k is known and is obtained by swapping as long as possible a "large" subset from the current solution by a set with one more element. Here we give a simple analysis of the more particular two-for-one repeated swapping heuristic, obtaining a (weaker) 2/(k+1)-approximation.

Authors: Adrian Calinescu, Gruia Calinescu

Let f:2^N --> \cZ^+ be a polymatroid (an integer-valued non-decreasing submodular set function with f(emptyset) = 0). A k-polymatroid satisfies that f(e) <= k for all e in N. We call a subset S of N independent if f(S) equals the sum of f(e) over the elements e of S and f(e) > 0 for all e in S. Finding a maximum-size independent set in a 2-polymatroid has been studied and polynomial-time algorithms are known for linear polymatroids. For k >= 3, the problem is NP-hard, and an approximation algorithm with ratio approaching 2/k is known and is obtained by swapping as long as possible a "large" subset from the current solution by a set with one more element. Here we give a simple analysis of the more particular two-for-one repeated swapping heuristic, obtaining a (weaker) 2/(k+1)-approximation.

Thursday, October 08 2026, 00:00

A faster matrix multiplication algorithm through structured optimization

Authors: Reza Zadeh

We present a new asymptotic matrix multiplication construction yielding $ω<2.37115924$, and therefore an algorithm that multiplies two $n\times n$ matrices in $O(n^{2.37115924})$ arithmetic operations over the rationals, reals, or complex numbers. The construction improves the bound $2.371177$ of Dupont et al. within the combination-loss framework for the Coppersmith--Winograd tensor. Our approach combines a shared recursive parameter family with a conditioned optimization procedure that addresses two obstacles: weak gradients at low-mass constituents and competing bottlenecks in the retained exponent. A mass- and probability-dependent rescaling supports quasi-Newton optimization in $212\,820$ coordinates, while a six-control correction balances the three extraction roles at each relevant stage. Positive rational entropy-dual factors and an independent ordinary-string verifier turn the resulting construction into an exact certificate. The verified upper-bound expression lies in $[2.3711592385931075066123,\,2.3711592385931075066124]$. The complete witness and an offline verifier using only the Python standard library accompany the paper.

Authors: Reza Zadeh

We present a new asymptotic matrix multiplication construction yielding $ω<2.37115924$, and therefore an algorithm that multiplies two $n\times n$ matrices in $O(n^{2.37115924})$ arithmetic operations over the rationals, reals, or complex numbers. The construction improves the bound $2.371177$ of Dupont et al. within the combination-loss framework for the Coppersmith--Winograd tensor. Our approach combines a shared recursive parameter family with a conditioned optimization procedure that addresses two obstacles: weak gradients at low-mass constituents and competing bottlenecks in the retained exponent. A mass- and probability-dependent rescaling supports quasi-Newton optimization in $212\,820$ coordinates, while a six-control correction balances the three extraction roles at each relevant stage. Positive rational entropy-dual factors and an independent ordinary-string verifier turn the resulting construction into an exact certificate. The verified upper-bound expression lies in $[2.3711592385931075066123,\,2.3711592385931075066124]$. The complete witness and an offline verifier using only the Python standard library accompany the paper.

Thursday, October 08 2026, 00:00

Dijkstra Is NOT Greedy: A Global-to-Local Proof of Correctness

Authors: Shengbao Wang

Dijkstra's algorithm is almost universally classified as a canonical greedy algorithm. This paper challenges that conventional interpretation and presents a simple, direct proof of correctness from a different viewpoint. Contrary to the widespread intuition that the algorithm repeatedly makes a local choice and thereby reaches a global optimum, we show that the logical direction can be read in exactly the opposite way: at each iteration, the algorithm identifies a globally shortest path among all paths whose destinations remain unsolved, and the endpoint of that globally shortest path is therefore solved as a ``local'' shortest-path problem. In other words, the local shortest path is obtained as an immediate consequence of a global minimum. Based on this observation, we formulate a Three-Step Exclusion Method that interprets Dijkstra's iteration as deterministic contraction of the global path space. The resulting proof highlights optimal substructure, boundary-state reduction, and dynamic-programming structure, and offers a conceptually simple alternative to the usual greedy explanation.

Authors: Shengbao Wang

Dijkstra's algorithm is almost universally classified as a canonical greedy algorithm. This paper challenges that conventional interpretation and presents a simple, direct proof of correctness from a different viewpoint. Contrary to the widespread intuition that the algorithm repeatedly makes a local choice and thereby reaches a global optimum, we show that the logical direction can be read in exactly the opposite way: at each iteration, the algorithm identifies a globally shortest path among all paths whose destinations remain unsolved, and the endpoint of that globally shortest path is therefore solved as a ``local'' shortest-path problem. In other words, the local shortest path is obtained as an immediate consequence of a global minimum. Based on this observation, we formulate a Three-Step Exclusion Method that interprets Dijkstra's iteration as deterministic contraction of the global path space. The resulting proof highlights optimal substructure, boundary-state reduction, and dynamic-programming structure, and offers a conceptually simple alternative to the usual greedy explanation.

Thursday, October 08 2026, 00:00

Community and Company

from Sophie Huiberts

My community is under attack by commercial interests.

My community is under attack by commercial interests. Since last week, speedrun.com refuses to distribute our database of speedrun accomplishments under the agreed-upon Creative Commons license. This licensing dispute is a major breach of trust and an abdication of SRC's responsibilities to the community. Individual game's communities are all scrambling to find a new home for their leaderboards. SRC has the audacity to say its for our own good.

My other community is also under attack by commercial interests. OpenAI and Anthropic are telling their models to solve open mathematical problems, presumably to evaluate their models' capabilities. Sure, if that is productive then I won't judge that. What I do disapprove of, is that OpenAI is yeeting all their exhaust onto the internet.

When you prove a theorem, you are imparted a responsibility to the field. At minimum you need to explain what you did, including which steps required new ideas and which steps are already well-known. More substantively, you are expected to nurture the literature. If an important idea was poorly explained in its first incarnation, then you have to explain it better in your work. These demands are broadly accepted and are not controversial. Any time you meet the demands, the resulting paper is highly appreciated and valued.^[1] The responsibility is yours because you have the opportunity to publish a paper on the subject.

OpenAI is doing the exact opposite. They do not care about their 'manuscripts'. They don't bother putting in appropriate attribution of ideas, their work contains errors, and they don't even bother with consistent presentation or formatting. This actively sets back the state of the literature.

Why are they doing this? Is there a benefit to their releasing this exhaust? Does science benefit? OpenAI says these results took 3 hours of LLM time on average with their internal model. Likely their public models can achieve the same outcomes when instructed by expert guidance. That's why they keep scooping their own customers.^[2] A scooping that, I will add, is only possible because OpenAI outputs such sloppy work.

If an expert prompts a result, they take up the mantle of responsibility I describe above. OpenAI not only refuses to take their responsibility, but they prevent their own customers from doing so. And they have the audacity to say they do it for the good of science.

[1]

One example of such a valued paper is Daniel and I's smoothed analysis paper. Yes we proved better running time bounds, but mostly using ideas that were in the literature already. The contribution of the paper was that it was nice to read, unlike the notoriously opaque literature that came before it. It would have been difficult to justify the time we spent writing this all up nicely if we hadn't also improved the result quantitatively, hence the responsibility. The paper remains my most visible piece of work, still accruing more citations per year than later follow-up work.

[2]	Here is one example from today of OpenAI customers who got scooped because they were spending their time writing up a nice paper instead of staking a flag on github dot com.

Thursday, October 08 2026, 00:00

News for September 2026

from Property Testing Review

Dear PTReview readers, we are in the brave new world of LLM assisted math papers. The total number of papers we need to look through each month has almost tripled, so apologies if your paper get missed. Please email little.oh.of.n@gmail.com with a link to an arXiv or ECCC paper. In general, we would appreciate sending […]

Dear PTReview readers, we are in the brave new world of LLM assisted math papers. The total number of papers we need to look through each month has almost tripled, so apologies if your paper get missed. Please email little.oh.of.n@gmail.com with a link to an arXiv or ECCC paper. In general, we would appreciate sending us such an email as soon as your paper gets public, to make it easier for the editors to keep track of property testing papers.

We have a large collection of eleven (!!) papers, which we arrange by subtopic.

Query Complexity of Testing Structured Parenthesis Languages by Tim Jackman, Diptaksho Palit, and Sofya Raskhodnikova (arXiv). This paper and the next study the classic problem of testing Dyck languages, which are formed by correct parenthetical strings. When there is only one parenthesis type, then there are $O(poly(1/\varepsilon))$ query property testers. When there are two or more parentheses types, the complexity jumps to somewhere between $\Omega(n^{1/5})$ and $O(n^{2/5+\delta})$. This paper proves an (almost) optimal lower bound of $\Omega(n^{2/5})$, even for adaptive algorithms. A non-adaptive lower bound of $\Omega(n^{1/2})$ is also proven. In addition, the paper proves that complexity is $\Theta(\varepsilon^{-2})$ for single parenthesis type setting.

Near-Optimal Bounds for Testing Residual-String Equality and Parenthesis Languages by Hadar Strauss (arXiv). The primary result of this paper is the same: the adaptive $\Omega(n^{2/5})$ and non-adaptive $\Omega(\sqrt{n})$ lower bounds. This paper also shows a non-adaptive upper bound of $O(n^{1/2+\delta})$ (for any $\delta > 0$), and gives an improved dependence on $\delta$ for the adaptive setting. The lower bound constructions in both papers go via a “hidden” or “residual” string equality problem, wherein binary strings are padded with a dummy $*$ symbol. The aim is to determine properties of the binary string after the dummy symbols are removed.

Collision Detection is Instance $\widetilde{O}$ptimal Under the Birthday Threshold by Omri Ben-Eliezer, Tomer Grossman, Václav Rozhoň, and Jakub Tětek (arXiv). Consider the classic problem of collision detection in a function $f:[n] \to [n]$. So we want to find $x \neq y$ such that $f(x) = f(y)$. As our readers will likely know, if $f$ is random, a standard birthday paradox argument shows that $O(\sqrt{n})$ samples suffice. Suppose we knew something about the function $f$, such as the structural properties of $f$: then it is quite plausible we can beat the birthday paradox bound. This paper shows there is an instance optimal algorithm that is $O(\log n)$-competitive. This means, even if we design a tailormade algorithm that is optimized for a specific $f$, the algorithm of this paper will take at most $O(\log n)$ factor more queries. It is also known that this overhead cannot be beaten.

Testing the Binary Rank with Polynomial Query Complexity by Michal Parnas (arXiv). Consider an $n \times m$ Boolean matrix $M$. The binary rank is the smallest $d$ such that $M = AB$, where $A, B$ are Boolean matrices. And $A$ has dimension $n \times d$, and $B$ has dimension $d \times m$. The multiplication is done over the integers (not over $\mathbb{F}_2$, which would correspond to the Boolean rank). This paper studies the property testing version, where distance is naturally measure by (fractional) Hamming weight. The main result is an adaptive two-sided property testing, with query complexity $\widetilde{O}(d^3/\varepsilon^2)$. Previous results have query complexities exponential in $d$.

Testing Bipartite in the Bounded-Degree Graph Model, Revisited (A digest of the paper of Fei and Rubinfeld (2026)) by Oded Goldreich (ECCC). As the title says, this paper is an exposition of a recent Fei and Rubinfeld on a simpler analysis of the classic bipartiteness tester for Goldreich-Ron. It lays out the key differences of the Fei-Rubinfeld result, and gives an accessible explanation of the main ideas.

Private Graph Property Testing by Hendrik Fichtenberger, Abigail Gentle, Tamalika Mukherjee, Sayantan Sen (arXiv). Differential privacy (DP) and property testing have a lot in common. At its heart, DP is about the sensitivity of algorithms to their input. It feels like property testers should be differentially private, since they make inferences on the input by only sampling a small portion of the input. This paper makes the connections rigorous for graph property testing. For graph inputs, there are various notions of DP, called edge-DP and node-DP (depending on whether we want to preserve the privacy of node existence or edge existence). The paper provides a nice framework that connects graph property testers with DP. One of the main results, using canonical property testers for dense graphs, gives edge-DP and node-DP property testers for any property. The private query complexity is only a constant factor more than the non-private canonical tester. For bounded degree graphs, the paper gives a private version of the classic bipartiteness tester, using privacy preserving random walks. There are also results for hyperfinite graph properties.

On the Power of Adaptivity in Testing Quantum States in Fidelity by Jan Seyfried, Sayantan Sen, Marco Tomamichel (arXiv). This paper is on testing of quantum states, a topic that has seen much research over the past couple of years. This problem is the quantum equivalent of distribution testing: consider a known quantum state $\sigma$. Given input to an unknown quantum state $\rho$, we wish to distinguish $\rho = \sigma$ from $\rho$ being far from $\sigma$. Typical results measure distance in terms of a trace norm, but this paper focuses on an alternate distance notion called fidelity. For the original trace norm distance, various problems (certification, equivalence, and independence) all have basically the same complexity of $\widetilde{\Theta}(d^{3/2}/\varepsilon^2)$, where $d$ is the dimension of the quantum states. It was known that adaptivity does not help. For fidelity, the bounds change for the various problems, and adaptivity does give a provable improvement for equivalence and independence testing.

Distributed Quantum Property Testing with Quantum Carrier Pigeons by Kenny Chen, Mina Doosti, Ryan Sweke, Chirag Wadhwa (arXiv). This paper studies the same problem of quantum state testing, but in a distributed setting. Imagine that there are multiple nodes (called distributed nodes) that carry copies of the quantum state to be tested. They all communicate with a central node that has to solve the inference task. This model is inspired by a classic version of distributed distribution testing. There is a limit of classical bits ($n_c$) and qubits ($n_q$) that can be sent from each distributed node to the central node. When $n_q$ is larger than the number of qubits in the quantum state, the entire state can be sent to central node. The interesting case is when $n_q$ is smaller. This paper shows that with public randomness, there are non-trivial distributed algorithms, but there are lower bounds for private randomness.

Optimal Quantum State Testing Even with Limited Entanglement by Chirag Wadhwa, Sitan Chen (arXiv). Another paper on quantum state testing, but looking at the power of entanglement. The testing algorithms need to be multiple copies (or samples) of the input quantum state. But in previous optimal algorithms, these have to be entangled, which allows for a copy complexity $\widetilde{O}(d/\varepsilon^2)$. Without any entanglement, the complexity jumps by a quadratic factor. This paper studies what happens if the entanglement is limited to $t$. The complexity achieved is (essentially) $\widetilde{O}(d^2/\sqrt{t}\varepsilon^2)$, giving a smooth tradeoff between the extreme cases.

Good Quantum Locally Testable Codes from Product Expansion by Mitali Bafna, Anqi Li, and Quynh T. Nguyen (arXiv, ECCC). A locally testable code (LTC) is one for which the property of codewords has a constant query property tester. The tester is defined by a collection parity checks over subsets. A constant number of these checks are sampled uniformly at random to get the property tester. This paper shows that, assuming a conjecture about product expansion of Reed-Solomon codes over binary extension fields, there are quantum LTCs with constant rate, distance, soundness and locality.

Streaming Hypergraph Coloring via Palette Sparsification by Artur Czumaj, Pan Peng, Ruizhe Shi, Christian Sohler (arXiv). Formally, this is not a property testing paper, but palette sparsification is a fundamental tool in sublinear algorithms. So this is a good paper for our readers to check out. Let us leave aside the actual streaming results (which are interesting!). Palette sparsification is a technique where each vertex gets a subset of randomly sampled colors. One proves that there is a legal coloring where each vertex only picks from its “local palette”. This was a critical tool in sublinear graph coloring algorithms, and this paper generalizes the tool for hypergraphs. For coloring hypergraphs, we only need that no edge is monochromatic. One can prove that $\Theta(\Delta^{1/(k-1)})$ colors suffice for a proper coloring, where $\Delta$ is the maximum degree and all hyperedges have arity $k$. The main theorem shows that $\Theta(\sqrt{\log n})$ length lists suffice for each vertex.

By Seshadhri

Wednesday, October 07 2026, 19:17

The Mathocalypse

from Scott Aaronson

… then they came for Navier–Stokes and I said nothing because I never worked on Navier–Stokes. But when they came for RL vs. L I realized that things are serious –friend-of-the-blog Omer Reingold (shared with permission) Last night my 9-year-old son was taunting my wife, complexity theorist Dana Moshkovitz, as follows: “mommy, I heard you […]

… then they came for Navier–Stokes and I said nothing because I never worked on Navier–Stokes. But when they came for RL vs. L I realized that things are serious

–friend-of-the-blog Omer Reingold (shared with permission)

Last night my 9-year-old son was taunting my wife, complexity theorist Dana Moshkovitz, as follows: “mommy, I heard you got cooked! I heard that a robot solved the math problem you worked on for your whole career! OOF!”

While my son was being a brat, he also wasn’t wrong. Whether you’re thrilled, depressed, angry, or whatever else about it, yesterday was surely one of the biggest days in mathematical history. And yes, among the 372 huge results released yesterday by OpenAI, on the recommendation of its advisory group of Timothy Gowers, Edward Witten, and other distinguished mathematicians, was a proof of Subhash Khot’s Unique Games Conjecture (UGC), a statement that my wife has worked toward proving for the entire time I’ve known her. (The UGC implies that a whole slew of optimization problems really are NP-hard, even if you just want an approximation that’s slightly better than what you get from semidefinite programming relaxation, which is one of our main tools.)

Or at least, we’re pretty sure that it’s a proof! There’s a Lean certificate, as there are for some of the other 372 breakthrough results (not all of them). But it also appears that no human has understood just about any of these proofs yet; the race to do so has just started. If you want an on-the-ground sense of what that race is going to be like, here’s some of what Dana texted me last night:

It feels like something written by someone who’s on psychedelics. So much unclear and doesn’t make sense. Lots of name dropping of previous work without discussing why it can be used despite impossibility results

Basically the paper is so horribly written that it’s impossible to read it without AI help

I asked Astra for reasonable completeness and soundness claims of the noise gadget and it gave them by combining claims from all over the paper

They also have direct optimal NP hardness of approximation proofs for the main applications of the UGC (Max Cut and all CSP) that bypass the UGC.

The UGC proof invents a completely new bizarre code with a noise test. It’s some crazy recursive construction.

It’s not the long code, not the short code – some alien craziness

I still think that there maybe is a proof that uses the half space code (which is natural)

The citations are often irrelevant and confusing

A possible future is a math world that’s heavenly if you have vision/creative ideas that AI could help check and implement.

And of course there’s a lot for us to learn from the aliens

If you’re wondering what emotions Dana is feeling—well, probably all of them! Even while a central career aspiration has fallen to a robot, there are at least two mitigating factors for her. First, she can feel vindicated that the UGC was true after all, something she never doubted even while many of her colleagues did! Second, all of us in math and theoretical computer science and mathematical physics, at least those who cared about solving crisply-stated problems, are now in the same boat.

Besides the Unique Games Conjecture, here’s a small sampling of the treasures from Aladdin’s cave that I’ll probably be paying the most attention to over the coming weeks:

L=BPL (i.e., probabilistic logspace and deterministic logspace are the same thing), one of the great derandomization conjectures short of P=BPP. Though its truth was never in serious doubt, there was a whole subcommunity focused on proving this.
The Fourier Transform and integer multiplication in less than O(n log n) time, breaking a barrier that had stood since the 1960s. The new running time, if you’re curious, is O(n log^{0.9999999999999} n), give or take some 9’s.
Positive solution to the Unitary Synthesis Problem, which Greg Kuperberg and I posed back in 2007. For every n-qubit unitary transformation U, there exists a classical oracle A such that U can be implemented in quantum polynomial time with access to A. This is the opposite of what most of us expected, and could have implications for e.g. the computational problem of decoding Hawking radiation from a black hole and many other problems in quantum complexity theory—if we had an efficient way to construct the oracle A, which this paper doesn’t give. (Added: Here’s a beautiful blog post by friend and colleague Dakshita Khurana about the years she spent working on this problem—unlike me and most others, she believed correctly in a positive answer to it—and her current feelings as she works through the AI’s proof.)
Parity is not in QAC⁰, one of the great questions of quantum complexity theory since 1999 that many of my colleagues had been closing in on.
Nearly 4^th-power separation between randomized and quantum query complexity for total Boolean functions. A favorite problem of mine since 1998 (!), when we knew only that the optimal separating exponent was between 2 and 6. For the past few years, we knew it was between 3 and 4. So, this finally closes that story.
A superquadratic separation between sensitivity and block sensitivity.
Area law for 2D gapped Hamiltonians. One of the main open problems in Hamiltonian complexity.
Matrix multiplication in n^9/4+o(1) time—a rational exponent for once (!), and via a completely different approach than was used for O(n^2.373) and so forth
Ω(n3)\Omega(n^3) lower bound on the determinantal complexity of the permanent, improving the previous best bound which was quadratic.
A randomized polytime algorithm to approximately count the number of perfect matchings in a general graph, as well as a randomized nearly linear-time algorithm for finding a maximum matching in such a graph
Uncomputability of solving polynomial equations over the rational numbers—this was arguably the biggest open problem in computability theory (note that uncomputability of solving Diophantine equations, i.e. polynomial equations over the integers, was proved in the 1970s, giving a negative answer to Hilbert’s 10th Problem)

Any of the above, alone, could easily have been “result of the year” in some area (and in some cases, like Unique Games and L=BPL, in all of CS theory). And there’s a lot that I’ve left out—feel free to share in the comments whatever is making your eyes bug out! There are equally astounding wonders in number theory, combinatorics, algebraic geometry, analysis, and pretty much every other area of math, most of which I’ll never understand, although I’ll note that it includes partial progress toward the Riemann hypothesis and the Hodge Conjecture and the Birch-Swinnerton-Dyer Conjecture (i.e., the majority of the remaining Millennium Problems).

We can take solace in what’s missing from the list. P≠NP isn’t there, nor even P=BPP or NEXP⊄P/poly, and surely not for lack of trying. Apparently the greatest open problems of theoretical computer science are indeed pretty hard!

Oh, lest I forget: one day before the OpenAI dump, meaning Monday evening, Virginia Williams and Josh Alman posted an arXiv preprint that solves the 3SUM problem in O(n^1.9992) time, and the All-Pairs Shortest Paths problem in O(n^2.9995) time, refuting half-century-old conjectures that the correct answers were n^2-o(1) and n^3-o(1) respectively. In this case, it wasn’t an OpenAI model that supplied the crucial idea; it was an Anthropic one! But Anthropic then took a different approach from OpenAI: rather than post the undigested solutions to the world, it gave Virginia and Josh the opportunity to write and announce a digested version in exchange for compensation.

These have emerged as the two main models for communicating AI math breakthroughs, and they both have strengths and weaknesses. The “OpenAI model” sets up a crazy race among humans to digest and explain a messy AI proof (work that could easily be some combination of thankless, barely-credited, competitive, and unfun), while the “Anthropic model” puts a private company in the position of picking and choosing which human mathematicians get to be the emissaries of the AI. Dunno, what do you guys think?

For those who are wondering: apparently, the AI model that produced all these wonders was not bespoke contraption of 10,000 agents burning millions of dollars worth of compute, as was used for example to construct a finite-time blowup for the Navier-Stokes equations. Instead, it was simply the latest internal OpenAI model—one that might be released to paying ChatGPT customers within the next couple of months, depending on the recommendations of OpenAI’s safety board! (My 9-year-old son: “Oh they definitely shouldn’t release that. If it could solve all those math problems, it can’t possibly be safe.”) Apparently they used about 3 hours of GPT-Pro level compute on average per problem solved.

Also, if you were wondering: apparently they tried the model on about 8,000 problems. So, right now it “merely” solves ~5% of the longstanding open mathematical problems that it’s asked about, the problems that whole communities have spent years on, after a single 3-hour attempt on them.

I’ve been glad to see the CS theory community rising to the occasion. At the Simons Institute in Berkeley, here at UT Austin, and elsewhere, I’ve hearing stories of researchers rushing to pore over the manuscripts and make sense of them and explain them—because what else do we do? How else do we continue the craft to which we’ve devoted much of our lives?

If you want some sense of what things feel like now in math, imagine a hunter-gatherer who’s spent his entire life learning to survive deep in an unforgiving rainforest, then a giant resort hotel springs up right next to him with a helipad and heated pools and AirBnBs, and without missing a beat, the hunter-gatherer says: “alright fine, so now my new job is to run wilderness retreats for the tourists, or something.”

In Quanta magazine, Jordana Cepelewitz attempted a different metaphor:

It’s as if you were teleported to the peak of a tall mountain. Surrounded by fog, you have no idea where you are, or what’s around you. You do not know how your mountain connects to others, and you have no equipment to help you explore, no way to help someone else join you. If you had climbed the mountain yourself, you would have experienced how the human body adapts to altitude and changes in oxygen levels. You might have had to invent tools to navigate, to climb steep cliffs, or to make a shelter. You might have encountered a fellow explorer, gotten lost together in a hidden valley, and found a plant that could be turned into a life-saving medicine.

Instead you’re perched on the peak but in the dark, while the maker of the teleportation machine tells you that it can explore the wilderness better than any human.

For any one of these mountains, if we care enough, I feel optimistic that we can do as we always have: clear the fog and figure out the path, except now using the teleportation machine to help guide us. The bigger challenge will be to nurture a community that still cares about the heroic adventure of finding the paths up these mountains in the world with the machine. (Oh, and I think one place where the metaphor breaks is that we still do have each other, as much as we ever did before!)

Experience has shown that, even now, there will still be people explaining in patronizing tones why none of this is real and none of it counts. If such people were capable of being impressed by anything that happens in the empirical world, of updating on anything, they would’ve already been impressed and already updated several years ago, long before things had reached the point of an actual Mathocalypse.

So, they’ll say, maybe the alleged solutions are not solutions at all, but just “AI slop.” Or maybe none of the 372 well-known open problems that were solved were real math problems, they were all just glorified contest puzzles and trivialities. (After all, there’s still no Riemann Hypothesis!) Or maybe the entire 4000-year-old discipline of mathematics needs to be jettisoned: turns out that it was all just puzzle-solving and trivialities; all that’s different is that now the triviality stands unmasked. In any case, what really matters is that the true inner sanctum of human creativity hasn’t been breached and probably never will be, and also, that Sam Altman and Dario Amodei are contemptible little nerds.

If you’re still a proponent of that doomed worldview, still aboard the sinking ship, I encourage you in the strongest possible terms to read yesterday’s other great contribution to AI discourse, besides the OpenAI Mathocalypse dump: namely, Scott Alexander’s open letter to Steven Pinker. I feel some responsibility for this, as the person who first introduced Steven Pinker to the existence of the rationalist community, and who also first introduced Steven Pinker and Scott Alexander to one another (they had both been fans of each other’s writing). And now Scott is challenging Steve to a literal duel, with guns!

For whatever it’s worth: Steve is a lifelong intellectual hero of mine, just as he is for Scott, and I also have to privilege of calling Steve my friend. But I found Scott’s post to be one of the most devastating rejoinders to anything that I’ve ever read. And I thought Scott’s conclusion was exactly right: when it comes to AI risk, Steve’s great challenge is now to accept and start using a more “Pinkerite” epistemology.

Last night, while I should’ve been poring over some of OpenAI’s hundreds of papers and/or writing this post, I decided to spend some time with my kids instead. They wanted a movie night, so I suggested something they’d never seen before (and that I hadn’t seen for decades), and that seemed chock-full of no-nonsense, practical guidance for the world in which they’re going to grow up: Terminator 2.

Update: As several people have pointed out, cryptography is a subfield that’s extremely conspicuous by its absence from OpenAI’s list of 376 papers! But my sources tell me that the AI companies have now started, gingerly and discreetly, investigating whether their latest internal models can break important cryptographic protocols and primitives. If they can, then it would certainly be nice to get ahead of things before the rest of the world figures out the same.

Another Update: The statement put out the Advisory Group on Mathematics and Artificial Intelligence is very carefully phrased, neither endorsing nor condemning what OpenAI did, and is worth a read:

As announced a few weeks ago, OpenAI has released a large collection of mathematical results generated by an internal model, reporting solutions to hundreds of open questions. This is an important event for mathematics, with consequences both for mathematics and for the mathematical community that extend far beyond the individual results.

AGMAI’s advisory role should not be interpreted as a judgment of the impact of these results or an endorsement of the process by which OpenAI obtained them. We do not speak on behalf of the entire mathematical community, and only the mathematical community can undertake the assessment that is needed.

Making this work public is a first step. This release is the beginning, not the completion, of the process of human understanding and the incorporation of the work into mathematical knowledge. At the same time, the future of mathematical research cannot consist only of understanding results produced by AI labs. Mathematicians must be able to formulate their own questions, develop their own approaches, and explore directions that have not been selected as examples of an AI system’s capabilities. Equitable access to powerful research tools and adequate computational resources are essential to that freedom.

We reaffirm our published recommendations on responsible release. We have discussed them with OpenAI and appreciate the company’s willingness to engage. While we consider these discussions constructive, it is ultimately up to the mathematical community to assess the extent to which our recommendations were followed successfully, and whether there are others we should suggest. We remain committed to engaging with any frontier AI lab on these questions and have already been in contact with several of them.

By Scott

Wednesday, October 07 2026, 18:57

OpenAI Math Dump Hits My Home

from Hung Le

Recent OpenAI Math dump have solutions to many long standing probems in Math and TCS. In the dump, two problems that I and my friends, notably Arnold Filtser, have studied for more than a decade, and published a few papers about this: The $\ell_1$-embedding conjecture for planar graphs. Open AI solution here. The $\ell_1$-embedding conjecture for bounded treewidth graphs. Open AI solution here.

Recent OpenAI Math dump have solutions to many long standing probems in Math and TCS. In the dump, two problems that I and my friends, notably Arnold Filtser, have studied for more than a decade, and published a few papers about this:

The $\ell_1$-embedding conjecture for planar graphs. Open AI solution here.
The $\ell_1$-embedding conjecture for bounded treewidth graphs. Open AI solution here.

It is unsettling and hard to swallow. I have not looked at the details yet, and will be doing so in the next few days. On a positive note, I hope to learn new techniques in planar graphs. I always believe that we have not been able to solve these problems because we lack a serious understanding of planar metrics. Now that they are solved, learning what the serious understanding is exciting.

A clear next prediction (not included among Open AI solution) is a solution of the conjecture that that minor-free graph metrics are embeddable into $\ell_1$ with constant distortion. Using the Robertson-Seymour decomposition, one basically could reduce this conjecture to bounded treewidth and planar graphs. At this point, I feel that understanding the two results above are more important than churning out another result.

Will udpate my understsanding of the two papers above.

I intentially do not mention other big results. What a strange time to be alive.

Updates:

Oct 08: Read the L1 embedding planar for 5 hours. Now that I understand the column model better, the lemmas in the first 12 pages are straightforward. I spent a lot of time figuring out what the statements of these lemmas actually mean. The proofs are straightforward, and nothing deep happens yet. I also spent about 3 hours reading section 3 of the manuscript. It is only 4 pages long, but full of gibberish. The central concept in this section is called a chart. Nothing in this section is formal: I have to interact with GPT Anstra just to understand what each paragraph means. So far, I get the impression that nothing deep happens in this section either. Perhaps great stuff will be in subsequent sections, so I am looking forward to that. It has been a lot of pain going through Sections 2 and 3.
Oct 07: Read planar L1 Embedding manuscript of Open AI for about 6 hours, gone through the details of the first 12 pages. The proof introduces a very strange model called the non-crossing column model of planar graphs, that I have not seen before. I have not yet internalized the model but got a “feel” for it. The writing is so compressed and dense. The expanded version (obtained by querying ChatGPT Astra) has 90+ pages. The “length” of the manuscript released by Open AI is cheated.

By Hung Le

Wednesday, October 07 2026, 18:35

TR26-233 | Trading Time, Space, and Alternations: General Plasticity for Algorithms from Hardness of Range Avoidance | Zeyong Li, Roei Tell

from ECCC Papers

In a recent breakthrough, Williams (STOC 2025) showed that any decision problem solvable in time $t$ by a multitape Turing machine can be solved in space $\tilde{O}(\sqrt{t})$ and time $2^{\tilde{O}(\sqrt{t})}$. The immediate question is whether this result is an anomaly, or an inherent feature of computation more generally. In this work we provide evidence that the resource trade-offs phenomenon first demonstrated by Williams is systematic, i.e. inherent to computation in general. Specifically, under a plausible complexity-theoretic hardness assumption, we show that $t$-time algorithms can be simulated in space $t^{\epsilon}$, for any constant $\epsilon>0$, where the simulation is correct on average over a random input. We also show, under similar complexity-theoretic hardness assumptions, that $t$-time algorithms can be simulated in \emph{linear time} using sufficiently many alternations (i.e., $\forall/\exists$ quantifiers), where again the simulation is correct on average over a random input. Some hardness assumption is necessary to prove these conclusions (as they imply that $\mathsf{P}\ne\mathsf{PSPACE}$), and the specific hardness assumption that we rely on has been extensively studied in complexity theory in recent years: hardness of a computational problem called Range Avoidance. Specifically, we introduce a new ``low-space'' variant of Range Avoidance, and show (under mild derandomization assumptions) that average-case hardness of this problem for polynomial-time algorithms is in fact \emph{equivalent} to low-space simulation of $\mathsf{FP}$, and implies linear-time simulation with alternations. We then study the complexity of this new problem, showing conditional hardness results and algorithms.

Wednesday, October 07 2026, 15:42

Open No More

from Computational Complexity

I wrote the post below last week. That was a quaint and quiet time. Last night OpenAI released a treasure trove of 722 manuscripts solving 372 major open problems in mathematics including from theoretical computer science:

A proof of the unique games conjecture (formalized in Lean)
A full derandomization of randomized log space
Matrix multiplication in $n^{2.25+\epsilon}$ time (formalized in Lean)

And many many more. I had Claude put together a webpage to make it easier to explore the TCS-related results.
Now these proofs haven't been fully verified but if they hold up, we've seen more progress in theoretical computer science in the last 24 hours than in the previous three decades combined!
It will take a while to process all these results, and what it means to the field of theoretical computer science and those who work within it. Much more in future posts.
A few caveats. As incredibly impressive as this work is, AI isn't solving everything--it solved under 10% of the problems given to it. And none of these results get us any closer to settling P v NP.
Nevertheless this will be a day we will never forget. Now on to my original post of far less important results.

Back in January, Matt Kovacs-Deak, Daochen Wang and Rain Zimin Yang solved my open question about the decision tree complexity of rational functions. With the help of AI some of my other open questions are continuing to get solved.

Adam Bouland, Andrew Huang, Anand Natarajan, Itay Shalit and Avishay Tal posted a paper giving an oracle where $\mathrm{BQP}$ is not in $\mathrm{IP}$ (interactive proofs). Now $\mathrm{BQP}$ is in $\mathrm{IP}$ since $\mathrm{BQP}\subseteq\mathrm{PSPACE}=\mathrm{IP}$, but the $\mathrm{IP}=\mathrm{PSPACE}$ proof doesn't relativize and Bouland et al. show you can even get an oracle that puts $\mathrm{BQP}$ out of $\mathrm{IP}$.

The paper also states "Together with recent work due to Scott Aaronson, Anand Natarajan, Avishay Tal, and Ági Villányi, our work also gives the first oracle separation between IP and MIP, answering a question dating back to Fortnow's thesis." $\mathrm{MIP}$ is the set of languages with multi-prover interactive proofs.

When I saw this paper, I pulled my PhD thesis off the shelf and indeed on page 40 I wrote "What is the relation between MIP and IP? Is there, for instance, an oracle separating the two classes".

When I wrote the thesis in 1989 we didn't know yet that $\mathrm{IP}=\mathrm{PSPACE}$ and $\mathrm{MIP}=\mathrm{NEXP}$ so we really didn't have any idea whether multiple provers actually gave you more power than one prover. When László Babai, Carsten Lund and I proved $\mathrm{MIP}=\mathrm{NEXP}$ a year later, we had strong evidence that $\mathrm{IP}\neq\mathrm{MIP}$ since we believe that $\mathrm{PSPACE}\neq\mathrm{NEXP}$. However since the proof that $\mathrm{MIP}=\mathrm{NEXP}$ doesn't relativize either, the question of the oracle separation between $\mathrm{IP}$ and $\mathrm{MIP}$ remained open until the Bouland et al. paper.

Finally, Eshan Chattopadhyay, Pooya Hatami, Chin Ho Lee, Shachar Lovett, Avishay Tal and Emanuele Viola gave new exponential correlation bounds for polynomials. The authors use that bound to give a new pseudorandom generator against $\mathrm{AC}^0[\oplus]$ circuits.

When I saw the paper I realized one could use this generator to show that $\text{Almost-}\oplus\mathrm{P}=\mathrm{BPP}^{\oplus\mathrm{P}}$, answering a question I had wondered about in the 90s. Here $\text{Almost-}\oplus\mathrm{P}$ is the class of languages $L$ such that $L\in\oplus\mathrm{P}^R$ with probability one for a random oracle $R$. This in turn could be used to give an alternative proof of Toda's theorem. Ken Regan and Jim Royer showed that relative to a random oracle the polynomial-time hierarchy is contained in $\oplus\mathrm{P}$, so $\mathrm{PH}\subseteq\text{Almost-}\oplus\mathrm{P}=\mathrm{BPP}^{\oplus\mathrm{P}}$. It would take me a long time to work out and write up the details so I had Claude do it for me.

I still have many more open problems, see for example my survey of open oracle questions. I'd be happy to see them solved. Feel free to use AI but verify the proof. You too could get mentioned on this blog.

By Lance Fortnow

I wrote the post below last week. That was a quaint and quiet time. Last night OpenAI released a treasure trove of 722 manuscripts solving 372 major open problems in mathematics including from theoretical computer science:

A proof of the unique games conjecture (formalized in Lean)
A full derandomization of randomized log space
Matrix multiplication in $n^{2.25+\epsilon}$ time (formalized in Lean)

And many many more. I had Claude put together a webpage to make it easier to explore the TCS-related results.

Now these proofs haven't been fully verified but if they hold up, we've seen more progress in theoretical computer science in the last 24 hours than in the previous three decades combined!

It will take a while to process all these results, and what it means to the field of theoretical computer science and those who work within it. Much more in future posts.

A few caveats. As incredibly impressive as this work is, AI isn't solving everything--it solved under 10% of the problems given to it. And none of these results get us any closer to settling P v NP.

Nevertheless this will be a day we will never forget. Now on to my original post of far less important results.

Back in January, Matt Kovacs-Deak, Daochen Wang and Rain Zimin Yang solved my open question about the decision tree complexity of rational functions. With the help of AI some of my other open questions are continuing to get solved.

Adam Bouland, Andrew Huang, Anand Natarajan, Itay Shalit and Avishay Tal posted a paper giving an oracle where $\mathrm{BQP}$ is not in $\mathrm{IP}$ (interactive proofs). Now $\mathrm{BQP}$ is in $\mathrm{IP}$ since $\mathrm{BQP}\subseteq\mathrm{PSPACE}=\mathrm{IP}$, but the $\mathrm{IP}=\mathrm{PSPACE}$ proof doesn't relativize and Bouland et al. show you can even get an oracle that puts $\mathrm{BQP}$ out of $\mathrm{IP}$.

The paper also states "Together with recent work due to Scott Aaronson, Anand Natarajan, Avishay Tal, and Ági Villányi, our work also gives the first oracle separation between IP and MIP, answering a question dating back to Fortnow's thesis." $\mathrm{MIP}$ is the set of languages with multi-prover interactive proofs.

When I saw this paper, I pulled my PhD thesis off the shelf and indeed on page 40 I wrote "What is the relation between MIP and IP? Is there, for instance, an oracle separating the two classes".

When I wrote the thesis in 1989 we didn't know yet that $\mathrm{IP}=\mathrm{PSPACE}$ and $\mathrm{MIP}=\mathrm{NEXP}$ so we really didn't have any idea whether multiple provers actually gave you more power than one prover. When László Babai, Carsten Lund and I proved $\mathrm{MIP}=\mathrm{NEXP}$ a year later, we had strong evidence that $\mathrm{IP}\neq\mathrm{MIP}$ since we believe that $\mathrm{PSPACE}\neq\mathrm{NEXP}$. However since the proof that $\mathrm{MIP}=\mathrm{NEXP}$ doesn't relativize either, the question of the oracle separation between $\mathrm{IP}$ and $\mathrm{MIP}$ remained open until the Bouland et al. paper.

Finally, Eshan Chattopadhyay, Pooya Hatami, Chin Ho Lee, Shachar Lovett, Avishay Tal and Emanuele Viola gave new exponential correlation bounds for polynomials. The authors use that bound to give a new pseudorandom generator against $\mathrm{AC}^0[\oplus]$ circuits.

When I saw the paper I realized one could use this generator to show that $\text{Almost-}\oplus\mathrm{P}=\mathrm{BPP}^{\oplus\mathrm{P}}$, answering a question I had wondered about in the 90s. Here $\text{Almost-}\oplus\mathrm{P}$ is the class of languages $L$ such that $L\in\oplus\mathrm{P}^R$ with probability one for a random oracle $R$. This in turn could be used to give an alternative proof of Toda's theorem. Ken Regan and Jim Royer showed that relative to a random oracle the polynomial-time hierarchy is contained in $\oplus\mathrm{P}$, so $\mathrm{PH}\subseteq\text{Almost-}\oplus\mathrm{P}=\mathrm{BPP}^{\oplus\mathrm{P}}$. It would take me a long time to work out and write up the details so I had Claude do it for me.

I still have many more open problems, see for example my survey of open oracle questions. I'd be happy to see them solved. Feel free to use AI but verify the proof. You too could get mentioned on this blog.

By Lance Fortnow

Wednesday, October 07 2026, 15:42

Intersection Homology and Combinatorics

from Gil Kalai

This is a draft lecture notes written under my guidance for today’s lecture. Blue text represent my further comments.) The lecture will be on Oct 7 at IAS, at 3:30, in the Seminar room. I will speak at the IAS … Continue reading →

This is a draft lecture notes written under my guidance for today’s lecture. Blue text represent my further comments.) The lecture will be on Oct 7 at IAS, at 3:30, in the Seminar room.

I will speak at the IAS about the wonderful theory of intersection homology, introduced by Mark Goresky and Bob MacPherson, and some of its connections to combinatorics. This post is an extended description of the lecture and a set of notes toward it. I would like to explain the basic definitions, then discuss three directions that particularly interest me: the missing ring structure behind toric $g$ -vectors, the search for intersection homology in face rings, and extensions involving several perversities.

These questions continue discussions from the pleasant informal seminar we had here in 1995 with Bob MacPherson, Mark Goresky, Tom Braden, and a few others. I will try to keep the discussion self-contained and easygoing. Throughout, coefficients are rational unless another field is specified.

I will start by briefly discussing convex polytopes $P$ , the parameter $g_2(P)$ , rigidity, and the theorem of Walter Whiteley.

1 Intersection homology and Poincaré duality

For a closed oriented manifold of dimension $N$ , Poincaré duality gives a perfect pairing between homology in degrees $i$ and $N-i$ . Singular spaces need not satisfy this duality. Intersection homology repairs it by controlling the way chains meet the singularities.

Start with a stratified pseudomanifold, with filtration

$\displaystyle X=X^N\supseteq X^{N-1}=X^{N-2}\supseteq\cdots\supseteq X^0\supseteq X^{-1}=\varnothing.$

The strata are manifolds, the top stratum is dense, and a neighborhood of a point in an $s$ -dimensional stratum looks like $\mathbb R^s\times cL$ , where $cL$ is the open cone on a compact link. We initially exclude codimension-one strata.

A traditional perversity is an integer function $\bar p$ satisfying

$\displaystyle \bar p(2)=0,\qquad \bar p(c)\leq\bar p(c+1)\leq\bar p(c)+1.$

For a PL $i$ -chain $\xi$ , the allowability condition is

$\displaystyle \dim\bigl(|\xi|\cap X^{N-c}\bigr)\leq i-c+\bar p(c),\qquad c\geq2.$

A negative bound means that the intersection must be empty. The chain and its boundary must satisfy their respective conditions. These chains form a complex $I^{\bar p}C_*(X)$ ; its homology is $I^{\bar p}H_*(X)$ . One uses compatible subdivisions in the PL construction. A singular-chain formulation instead requires

$\displaystyle \sigma^{-1}(X^{N-c})\subseteq \operatorname{sk}_{i-c+\bar p(c)}\Delta^i$

for every simplex occurring with nonzero coefficient in the chain or its boundary. Requiring the boundary to be allowable is essential: allowable simplices alone do not form a chain complex. [1, 2]

Why do complementary perversities occur? If chains of dimensions $i$ and $j$ meet a codimension- $c$ stratum in their allowed dimensions, a general-position intersection there has dimension at most

$\displaystyle i+j-N-c+\bar p(c)+\bar q(c).$

For $i+j=N$ and $\bar p(c)+\bar q(c)=c-2$ , this bound is $-2$ . Thus complementary cycles can intersect in the regular part, where signed intersection numbers make sense.

The theorem of Goresky and MacPherson says that, for a compact oriented pseudomanifold without boundary and complementary traditional perversities, this produces a perfect pairing

$\displaystyle I^{\bar p}H_i(X;\mathbb Q)\times I^{\bar q}H_{N-i}(X;\mathbb Q)\longrightarrow\mathbb Q.$

Traditional intersection homology is independent of the chosen suitable stratification. On a manifold it recovers ordinary homology. These are substantial theorems: the definition itself visibly uses the strata. [1, 2]

The cone as a first example

Let $L$ be a connected closed manifold of dimension $\ell\geq1$ . For the cone stratification, the finite-chain cone formula, in positive degrees, is

$\displaystyle I^{\bar p}H_i(cL)= \begin{cases} H_i(L),&i<\ell-\bar p(\ell+1),\\ 0,&i\geq\ell-\bar p(\ell+1). \end{cases}$

The zeroth group is $\mathbb Q$ . A cycle on the link becomes a boundary when its radial cone is allowable. For example, at a cone point of codimension three, $\bar p(3)=0$ prohibits a two-dimensional filling from meeting the vertex, whereas $\bar p(3)=1$ permits it. This is a useful local calculation to keep in mind throughout the lecture. [1, 6]

2 Middle perversity and the missing ring

The two middle perversities are

$\displaystyle \bar m(c)=\left\lfloor\frac{c-2}{2}\right\rfloor, \qquad \bar n(c)=\left\lceil\frac{c-2}{2}\right\rceil.$

They are complementary. They agree in even codimension and differ by one in odd codimension. A complex algebraic variety admits a stratification with even real codimensions, so the distinction disappears there. Middle intersection homology is consequently self-dual. For projective varieties it also has a hard Lefschetz theorem, with the action of an ample class. [2]

Toric h and g vectors

Here is a combinatorial definition that fixes our convention. For a $d$ -polytope $P$ , recursively define

$\displaystyle h(P,t)=\sum_{F\subsetneq P}g(F,t)(t-1)^{d-1-\dim F},$

including the empty face, with $\dim\varnothing=-1$ and $g(\varnothing,t)=1$ . For a point, $h(P,t)=1$ . Write

$\displaystyle h(P,t)=\sum_{i=0}^d h_i(P)t^i, \qquad g(P,t)=\sum_{i=0}^{\lfloor d/2\rfloor} \bigl(h_i(P)-h_{i-1}(P)\bigr)t^i,$

where $h_{-1}=0$ . These are the toric h and g vectors, extending the usual simplicial definitions. For a polygon with $v$ vertices, the recursion gives

$\displaystyle h(P,t)=1+(v-2)t+t^2,\qquad g(P,t)=1+(v-3)t.$

For rational $P$ , place the origin in its interior and take the fan of cones over its proper faces. Its projective toric variety $X_P$ has

$\displaystyle h_i(P)=\dim IH^{2i}(X_P;\mathbb Q),\qquad IH^{2i+1}(X_P;\mathbb Q)=0.$

This convention uses the face fan of $P$ , equivalently the normal fan of its polar. Using the normal fan of $P$ itself gives the convention for the dual polytope.

Duality gives $h_i=h_{d-i}$ ; hard Lefschetz gives $g_i\geq0$ . Combinatorial intersection cohomology of fans extends the theory beyond rational polytopes, and Kalle Karu proved hard Lefschetz in that generality. [3]

The paper of Tom Braden and Bob MacPherson, Intersection homology of toric varieties and a conjecture of Kalai, proves my monotonicity conjecture for rational polytopes using intersection homology. Braden’s subsequent paper, Remarks on the combinatorial intersection cohomology of fans, explains the extension to arbitrary polytopes, further properties of toric $g$ -vectors, and the connection between $g_2$ and rigidity. [11, 12]

There is also a striking relation between a four-dimensional polytope and its polar: $latex g_2(P)=g_2(P^)$. I discussed it in my post A Mysterious Duality Relation for 4-dimensional Polytopes. Braden’s work places such relations in a broader framework involving exact sequences and Koszul duality. Stanley’s Subdivisions and local h-vectors* is another central reference: it develops local invariants of subdivisions and identities connecting the toric invariants of dual face lattices. [12, 13, 14]

But there is a further question. Is the toric g vector of every convex polytope an M-sequence? That means it is the Hilbert function of a standard graded algebra:

$\displaystyle A=\bigoplus_{i\geq0}A_i,\qquad A_0=\mathbb Q, \qquad A\text{ generated by }A_1, \qquad \dim A_i=g_i(P).$

This asks for more than nonnegativity. Macaulay’s inequalities constrain the growth of such a Hilbert function; already

$\displaystyle g_2\leq\binom{g_1+1}{2}.$

For a simplicial polytope, its Stanley–Reisner ring provides the mechanism: take an Artinian reduction by a linear system of parameters, then quotient by a Lefschetz linear form. The Hilbert function of this last quotient is the $g$ -vector.

For a general polytope we have intersection cohomology and Lefschetz operators, but no natural internal multiplication on fixed middle-perversity intersection cohomology that supplies this argument. There are products involving different perversities, and an action of ordinary cohomology; neither automatically gives the needed standard graded algebra. This is the missing ring problem. A suitable substitute might be enough: an algebra realizing the primitive dimensions, or another mechanism enforcing Macaulay’s inequalities. The numerical M-sequence question and the construction of a geometrically meaningful multiplication are related, but distinct problems.

I discussed the search for a product—or a weaker substitute, perhaps resembling a Massey product—in my 2004 report, Combinatorial expectations from commutative algebra. This remains a useful reference for the missing ring problem and its broader combinatorial motivation. [17]

3 Witt spaces and an upper bound conjecture

Paul Siegel’s Witt condition enlarges the class of spaces with self-dual middle intersection homology beyond spaces with only even-codimension singularities. At every singular stratum of odd codimension $2a+1$ , its link $L$ has dimension $2a$ . The rational Witt condition is

$\displaystyle I^{\bar m}H_a(L;\mathbb Q)=0.$

On a Witt space the natural comparison from lower-middle to upper-middle intersection homology is an isomorphism. Compact oriented Witt spaces therefore have a self-dual middle theory. The condition is local and depends on the coefficient field. [4]

For a concrete example, the cone on a two-torus fails the Witt condition because $H_1(T^2;\mathbb Q)=\mathbb Q^2$ . The cone calculation gives lower-middle $IH_1=\mathbb Q^2$ and upper-middle $IH_1=0$ . In contrast, the cone on $S^2$ satisfies the condition. The obstruction is precisely the middle homology of the link.

Paul Howard Siegel developed Witt spaces in his 1979 MIT thesis, with crucial guidance from Mark Goresky. Goresky introduced him to the problem, and their conversations were central to its solution. Edward Y. Miller was the formally listed thesis supervisor. Siegel’s paper appeared in 1983. His later career took him into information theory, coding, and data storage, through IBM Research and UC San Diego. I find this a lovely connection between a beautiful idea about singular spaces and a quite different area of mathematics and engineering. [5]

The upper bound theorem says that a $d$ -polytope with $n$ vertices has no more $i$ -faces than the cyclic polytope $C_d(n)$ . Here is the simplicial Witt-space conjecture I would like to discuss:

Conjecture. Let $K$ triangulate a compact oriented Witt pseudomanifold of dimension $d-1$ , with $n$ vertices. If $d-1=2a$ is even, additionally assume $I^{\bar m}H_a(K;\mathbb Q)=0$ . Then $\displaystyle f_i(K)\leq f_i\bigl(\partial C_d(n)\bigr),\qquad 0\leq i\leq d-1.$

The global vanishing assumption is additional to the local Witt condition. Every closed oriented manifold is a Witt space, so the local condition alone cannot impose all cyclic-polytope bounds. For example, the seven-vertex triangulation of the torus has 21 edges, while the boundary of a three-dimensional cyclic polytope with seven vertices has 15.

Novik proved the bound for even-dimensional manifolds with vanishing middle homology. Her ICM survey states the Witt-space conjecture and discusses further cases and stronger upper-bound questions. The hoped-for bridge is an algebraic interpretation of intersection homology that interacts with face enumeration. [7]

4 Looking for intersection homology in face rings

Let $K$ be a simplicial complex on $[n]$ . Its symmetric face ring is

$\displaystyle \mathbb Q[K]=\mathbb Q[x_1,\ldots,x_n]/I_K, \qquad I_K=(x_{i_1}\cdots x_{i_r}:\{i_1,\ldots,i_r\}\notin K).$

Its exterior face ring is

$\displaystyle E[K]=\bigwedge\langle e_1,\ldots,e_n\rangle/J_K, \qquad J_K=(e_{i_1}\wedge\cdots\wedge e_{i_r}:\{i_1,\ldots,i_r\}\notin K).$

Both record faces; their additional algebraic structures record much more.

In the exterior ring there is a particularly direct illustration. Multiplication by $f=e_1+\cdots+e_n$ gives a differential $u\mapsto f\wedge u$ , since $f\wedge f=0$ . Its cohomology in degree $r$ is the reduced simplicial cohomology $\widetilde H^{r-1}(K;\mathbb Q)$ : the monomial basis is the face basis, and the differential adds one vertex with the usual signs. Thus ordinary cohomology already lives in this algebra.

On the symmetric side, local cohomology and graded resolutions encode the homology of links and induced subcomplexes. For triangulated manifolds, Schenzel’s formula and the work of Novik and Swartz show how ordinary Betti numbers enter Artinian reductions and their socles. These results provide models for what one might seek for intersection homology. [8, 9]

The question is to recover, for each traditional perversity,

$\displaystyle I^{\bar p}H_*(|K|;\mathbb Q)$

through algebraically defined complexes, subquotients, or filtrations associated with either face ring, without supplying a separate stratification. Here “arbitrary perversities” initially means arbitrary traditional Goresky–MacPherson perversities; more general stratum-dependent or superperversities require separate invariance hypotheses.

Merely recovering ordinary homology is insufficient. In the cone on the torus, ordinary positive-degree homology vanishes, while lower-middle intersection homology retains two degree-one classes. Any proposed face-ring construction must distinguish these phenomena.

A possible direction is to use generic linear forms and their flags to express allowability algebraically. On the exterior side this suggests kernels of contraction operators; on the symmetric side, Koszul complexes, annihilators, and local cohomology suggest candidates. These are research directions, not established replacements for the intersection-chain definition.

For the algebraic background, see also Braden’s Koszul duality for toric varieties and the paper with Valery Lunts, Equivariant-constructible Koszul duality for dual toric varieties. These concern categories of sheaves associated with dual cones; they provide a further connection between intersection cohomology and homological algebra. [15, 16]

There are several useful tests. On manifolds, a candidate must recover ordinary homology for every traditional perversity. On cones, it must reproduce the correct perversity-dependent truncation. It must survive subdivision and produce the complementary-perversity pairing. To help with upper bounds, it must also relate the resulting groups to dimensions or multiplication in the face ring. The last requirement is what makes this a combinatorial project rather than just another way to calculate topological groups.

5 Multiperversities and the project with Greg Friedman

Here I will talk about my (dubious) vision.

In our paper, A multiperversity generalization of intersection homology, Greg Friedman and I replace one perversity by a finite collection $J$ . Let $A_i^J$ be the span of singular $i$ -simplices allowable for at least one member of $J$ . Then

$\displaystyle I^JC_i(X)=A_i^J\cap\partial^{-1}(A_{i-1}^J), \qquad I^JH_i(X)=H_i(I^JC_*(X)).$

Different simplices may use different perversities, and the boundary may use different choices again. Consequently this is generally not the sum of the single-perversity intersection-chain complexes. If $J$ has a greatest member, the construction reduces to that member; incomparable perversities are the interesting case.

We established subdivision, Mayer–Vietoris, product results, and a cone formula. The paper left independence of stratification open. Its motivation was to find further invariants of singular spaces and, eventually, further combinatorial invariants of polytopes. [6]

Topological invariance is the central issue. An extra subdivision of a manifold must not create new invariants by adding artificial strata. More generally, the same underlying singular space, described by different suitable stratifications, should give canonically comparable groups. Henry King’s intrinsic-stratification approach gives a strategy; Greg’s later short proofs of ordinary intersection-homology invariance offer further guidance. [10]

One can see why collections of perversities introduce extra bookkeeping. For a link of dimension $\ell$ , define

$\displaystyle J_{\ell,i}=\{\bar p\in J:\ell-\bar p(\ell+1)\leq i\}.$

These are the labels under which an $i$ -cycle can be filled radially in the cone. As $i$ changes, the collection changes. One must therefore track the maps between theories for subcollections, not just the dimensions of the groups. Images of these maps can matter even when the separate groups are known.

The question is whether this local information can be assembled into a proof that the theory is unchanged under intrinsic aggregation of strata. A proposed proof must keep the comparison maps compatible with inclusions of collections, cone constructions, and the passage from local charts to the whole space. Duality for multiperversities is another question; it does not follow just by complementing each member of a collection.

I hope (do I really hope it?) these directions will eventually reinforce one another: more flexible topological invariants, algebraic constructions inside face rings, and new inequalities for face numbers. For the lecture, I would like to emphasize both the remarkable strength of the classical theory and the concrete questions that remain.

References and further reading

Mark Goresky and Robert MacPherson, Intersection homology theory, Topology 19 (1980), 135–162. Paper.
Mark Goresky and Robert MacPherson, Intersection homology II, Inventiones Mathematicae 72 (1983), 77–129. Paper.
Kalle Karu, Hard Lefschetz theorem for nonrational polytopes, Inventiones Mathematicae 157 (2004), 419–447. Preprint.
Paul H. Siegel, Witt spaces: A geometric cycle theory for KO-homology at odd primes, American Journal of Mathematics 105 (1983), 1067–1105. See also Greg Friedman, Intersection homology with field coefficients: K-Witt spaces and K-Witt bordism.
Siegel’s MIT thesis and UC San Diego biography.
Greg Friedman and Gil Kalai, A multiperversity generalization of intersection homology, Pure and Applied Mathematics Quarterly 3 (2007), 205–224. Author’s preprint.
Isabella Novik, Face numbers: the upper bound side of the story, ICM 2022; especially Section 5 and Conjecture 5.1. Survey.
Isabella Novik and Ed Swartz, Socles of Buchsbaum modules, complexes and posets, Advances in Mathematics 222 (2009), 2059–2084. Preprint.
Satoshi Murai, Isabella Novik, and Ken-ichi Yoshida, A duality in Buchsbaum rings and triangulated manifolds. Preprint.
Greg Friedman, Two short proofs of the topological invariance of intersection homology. Preprint.
Tom Braden and Robert MacPherson, Intersection homology of toric varieties and a conjecture of Kalai, Commentarii Mathematici Helvetici 74 (1999), 442–455. Preprint.
Tom Braden, Remarks on the combinatorial intersection cohomology of fans, Pure and Applied Mathematics Quarterly 2 (2006), 1149–1186. Preprint.
Richard P. Stanley, Subdivisions and local h-vectors, Journal of the American Mathematical Society 5 (1992), 805–851. Paper.
Gil Kalai, A Mysterious Duality Relation for 4-dimensional Polytopes, Combinatorics and more, June 6, 2018. Blog post.
Tom Braden, Koszul duality for toric varieties, Transactions of the American Mathematical Society 359 (2007), 385–415. Preprint.
Tom Braden and Valery Lunts, Equivariant-constructible Koszul duality for dual toric varieties, Advances in Mathematics 201 (2006), 408–453. Preprint.
Gil Kalai, Combinatorial expectations from commutative algebra, in Combinatorial Commutative Algebra, Oberwolfach Reports 1 (2004), Report 32/2004. Report

By Gil Kalai

Wednesday, October 07 2026, 13:36

Updates: Sharing AI progress on mathematics (amazing!); and my lecture plans

from Gil Kalai

With Danny and Sharon Kleitman and Michel Goemans at the MIT Endicott house. Sharing AI progress on mathematics (OpenAI) A few hours ago, Open AI shared solution to a few hundred mathematical problems. Certainly this is an amazing milestone for … Continue reading →

With Danny and Sharon Kleitman and Michel Goemans at the MIT Endicott house.

Sharing AI progress on mathematics (OpenAI)

A few hours ago, Open AI shared solution to a few hundred mathematical problems. Certainly this is an amazing milestone for mathematics, and the results will needs to be verified and digested by human mathematicians in the months to come. Several of the problems were discussed here on the blog over the past two decades and I will try to give a more detailed update regarding these problems and other “Math for AI” recent achievements. This is an amazing development!

Both the Open AI list and some news from colleagues from the last days are relevant to my lecture around Borsuk’s conjecture on Friday in Jeff-Fest.

My Lecture Tour

I am currently in the middle of a nostalgic and hectic tour, visiting Brown University, MIT, Yale, IAS, Rutgers (for Jeff Kahn’s conference celebration), and Princeton University. It is a pleasure to meet old friends and (both young and old) mathematicians that I did not meet before. I truly love both mathematics and the community of mathematicians, and I hope my lectures and posts reflect this feeling.

Right now I am writing from Avi and Edna’s home at the IAS, having just returned from a lovely mathematics department event welcoming the new academic year. Tomorrow, I will be speaking here about intersection homology and combinatorics. Later in the evening, I am giving a short lecture in the “discussion series” about my work on quantum computation, which I hope will spark an engaging conversation. It will be quite a challenge to present quantum computation and my two decades of research on the subject in a 20-to-30-minute lecture tailored for a general audience.

I also have a rather intense blogging plans: I am planning three posts based on my lectures: one on algebraic shifting at MIT, one on intersection homology and combinatorics at the IAS, and one on problems around Borsuk’s conjecture at “Jeff Fest.” Here is how I plan to go about it: I will feed an AI tool my abstract and a rough outline of the talk, and let it prepare detailed lecture notes that I can use for the presentation itself. (For the MIT talk, I only thought of this approach after the fact!) Later on, I will edit those lecture notes into blog posts. It is quite interesting—and a little amusing—to note that the AI writes not only about the technical matters but also attempts to capture “my” feelings and hopes.

I also plan a post with a candidate for “the most outrageous conjecture,” alongside an entertaining double-feature “test your intuition” post.

OpenAI’s New Mathematical Results: Connections to Earlier Posts

As I mentioned above, OpenAI released an impressive collection of mathematical results produced by an internal AI model: 722 manuscripts grouped into 372 families. Many of these concern problems that have appeared on this blog over the years.

Three disclaimers: first, the collection includes results with different stages of verification; their proofs will need to be checked and digested by the mathematical community. Second, even Lean verification may have issues, and third, there were a variety of other AI based results, also related to earlier blog posts that I did not collected; among those let me mention the Irrationality of $\zeta (5)$ , the Navier Stoke problem, The Komlos conjecture, Chvatal’s conjecture, and the KLS conjecture.

Here are twenty connections to earlier posts, with related results occasionally grouped together.

The Mahler conjectures. I discussed the symmetric Mahler conjecture and its connections to symplectic geometry and my conjectures on faces and flags. The release announces proofs of both the symmetric and general Mahler conjectures in every dimension, including the equality cases of Hanner polytopes and simplices, respectively.
Borsuk’s problem in dimension nine. The question of the smallest dimension admitting a counterexample to Borsuk’s conjecture has appeared here repeatedly, including in this 2023 update. The new manuscript gives a compact set in nine-dimensional Euclidean space that cannot be covered by ten sets of smaller diameter.
Hadwiger’s conjecture. In Combinatorics News I discussed Hadwiger’s conjecture, which relates graph coloring to complete minors, while reporting the disproof of its odd-minor strengthening. The new announcement gives counterexamples to the original conjecture, even among graphs with independence number at most two.
The chromatic number of the plane. In 2018 I reported Aubrey de Grey’s breakthrough showing that five colors are necessary to avoid monochromatic pairs at distance one. The new manuscript raises the lower bound to six, leaving six and seven as the two possible answers.
The Kakeya problem. My post on Hong Wang and Joshua Zahl’s breakthrough discussed the three-dimensional Kakeya set conjecture and the stronger maximal-function problem. The release announces the maximal conjecture in three dimensions and the Hausdorff-dimension conjecture in four dimensions.
Periodic tiling in dimension three. In An Aperiodic Monotile I also mentioned Greenfeld and Tao’s disproof of the periodic translational tiling conjecture. The new construction gives a finite translational tile in $\mathbb Z^3$ that admits no fully periodic tiling, reaching the smallest possible dimension for the lattice problem.
Covering density of convex bodies. I described the breakthrough of Ordentlich, Regev, and Weiss on efficient lattice coverings in this post. OpenAI announces a universal $O(n\log n)$ lattice-covering bound and matching examples even for unrestricted translative coverings, determining the worst-case order over convex bodies.
Distinct distances and unit distances. These problems featured in János Pach’s guest post on Guth and Katz and in my earlier extremal-combinatorics post. The release includes the sharp-order bound $c_d n^{2/d}$ for distinct distances in every fixed dimension $d\ge3$ and an improved planar unit-distance bound $O(n^{4/3-\delta})$ for some absolute $\delta>0$ .
Erdős’s arithmetic-progression conjecture. My post on Bloom and Sisask’s breakthrough discussed the three-term case of the assertion that divergent reciprocal sums force arithmetic progressions. The new result covers every finite length: any set of positive integers with divergent reciprocal sum contains arbitrarily long arithmetic progressions, with quasipolynomial quantitative bounds in Szemerédi’s theorem.
Sidorenko’s conjecture. I described Sidorenko’s conjecture, which predicts that a fixed bipartite graph has at least the density it would have in a random graph of the same edge density. The announced counterexample has 35 vertices and 66 edges and also disproves the related forcing conjecture.
Ryser’s covering conjecture. I discussed Ryser’s conjecture in my birthday post for Ron Aharoni, including his proof of the tripartite case. The new counterexamples are intersecting $r$ -partite, $r$ -uniform hypergraphs requiring $r$ vertices to meet every edge, whereas the conjecture predicts $r-1$ .
Crossing numbers of complete and complete bipartite graphs. These problems appeared in my discussion of Turán’s mathematics. The release reports proofs of the Harary–Hill and Zarankiewicz formulas, determining the minimum number of crossings in plane drawings of complete and complete bipartite graphs.
Barnette’s Hamiltonian-cycle conjecture. In Coloring Simple Polytopes and Triangulations I discussed Barnette’s conjecture that every cubic, bipartite, 3-connected planar graph has a Hamiltonian cycle. The new manuscript announces a proof of this conjecture.
Combinatorial invariance of Kazhdan–Lusztig polynomials. This was Problem 11 in my discussions of the G-programme, and I returned to it in a 2021 post about DeepMind’s mathematical work. The announced theorem says that isomorphic Bruhat intervals have the same equal-parameter Kazhdan–Lusztig polynomial, even when the intervals come from different Coxeter systems.
Ramanujan graphs and higher-dimensional expanders. The subject of New Ramanujan Graphs! returns with a deterministic polynomial-time construction of nonbipartite Ramanujan graphs, for every fixed degree at least three and every sufficiently large even number of vertices. In higher dimensions, the release announces bounded-vertex-degree coboundary expanders over $\mathbb F_2$ in every dimension at least three, continuing the theme of my introductory posts.
The second Kahn–Kalai conjecture and Talagrand’s conjectures. The release reports proofs of the second Kahn–Kalai conjecture, which bounds graph-containment thresholds using subgraph expectations, and of Talagrand’s discrete convexity conjecture, both discussed in my account of Jinyoung Park’s ICM lecture. A companion result makes integral and fractional expectation thresholds equivalent up to a universal constant.
The Friedgut–Kalai sharp-threshold conjecture. Sharp thresholds and the role of symmetry were central themes of Boolean Functions: Influence, Threshold, and Noise. The release announces the $O((\log n)^{-2})$ threshold-width bound for monotone graph properties between fixed intermediate probabilities, where $n$ counts vertices, together with the conjectured extension to uniform hypergraphs.
Unique Games and 2-to-1 Games. My 2018 post on the 2-to-2 Games Theorem discussed progress toward Khot’s conjectures and the issue of perfect completeness. The release announces a proof of the Unique Games Conjecture and, separately, the 2-to-1 Games Conjecture with perfect completeness.
Matrix multiplication. My post Cap Sets, Sunflowers, and Matrix Multiplication explored the connections between these problems. The new bound is $\omega\le9/4$ over the complex numbers, a substantial advance toward the conjecture $\omega=2$ .
Percolation: criticality and nonuniqueness. The release includes absence of infinite critical clusters for bond percolation on infinite connected locally finite quasi-transitive graphs with $p_c<1$ , extending the setting of my recent post on an AI proof of critical nonpercolation. It also announces $p_c<p_u$ for nonamenable graphs in this class, resolving the Benjamini–Schramm nonuniqueness conjecture discussed here in 2009.

A few more related posts

The logarithmic Brunn–Minkowski conjecture. My post The Logarithmic Minkowski Problem (2021) discussed the closely related existence problem for convex bodies with prescribed cone-volume data. The release announces a proof of the logarithmic Brunn–Minkowski conjecture for origin-symmetric convex bodies in every dimension.
The two-point Chowla conjecture. In EDP Reflections and Celebrations (2015), I discussed Tao’s logarithmically averaged Chowla and Elliott results and their role in solving the Erdős discrepancy problem. The new manuscript announces the ordinary two-point Chowla conjecture, giving cancellation in the Liouville correlations (\sum_{n\le X}\lambda(n)\lambda(n+h)=o(X)) for every fixed (h\ge1).
High-dimensional expanders. In High Dimensional Expanders: Introduction I (2011), I discussed several notions of expansion for simplicial complexes, including coboundary expansion. The new construction gives arbitrarily large complexes in every dimension (d\ge3), with bounded vertex degrees and uniform (\mathbb F_2) coboundary expansion in every degree below (d).
Amenability of Thompson’s group (F). My post The Thompson Group (2009) introduced the group of dyadic piecewise-linear homeomorphisms of the interval and highlighted the question of whether it is amenable. The new manuscript announces that Thompson’s group (F) is nonamenable.
Flat and ultraflat Littlewood polynomials. In Flat polynomials exist! (2019), I described the breakthrough of Balister, Bollobás, Morris, Sahasrabudhe, and Tiba and emphasized the remaining ultraflat problem for coefficients (\pm1). The new manuscript announces polynomials with (N) such coefficients whose modulus is ((1+o(1))\sqrt N) uniformly on the entire unit circle, answering that stronger question.
First-passage percolation. In Analysis of Boolean Functions week 5 and 6 (2013), I discussed passage-time fluctuations and the challenge of improving variance bounds in first-passage percolation. The release announces absence of doubly infinite geodesics in the planar model for i.i.d. nonnegative nonatomic weights whose minimum over four independent samples has finite second moment, and strict convexity and a continuously differentiable limit-shape boundary for exponential weights.

It is remarkable to see so many familiar questions in a single announcement. There is a great deal here to read, check, understand, and build on!

By Gil Kalai

Wednesday, October 07 2026, 02:35

On the Complexity of Mixed Equilibria in First-Price Auctions with Correlated Priors

Authors: Mark Chen, Xi Chen, Hao Cui, William Pires, Jonah Stockwell

We show that computing an approximate mixed Bayes-Nash equilibrium in a discrete first-price auction with correlated priors is PPAD-complete. The key intermediate step in our reduction is the PPAD-completeness of computing an approximate Nash equilibrium in a new normal-form game, the hypergraph discrete first-price auction, which may be of independent interest.

Authors: Mark Chen, Xi Chen, Hao Cui, William Pires, Jonah Stockwell

We show that computing an approximate mixed Bayes-Nash equilibrium in a discrete first-price auction with correlated priors is PPAD-complete. The key intermediate step in our reduction is the PPAD-completeness of computing an approximate Nash equilibrium in a new normal-form game, the hypergraph discrete first-price auction, which may be of independent interest.

Wednesday, October 07 2026, 00:00

Reed-Solomon Codes at Capacity: Algorithmic List-Decoding and Proximity Gaps

Authors: Prahladh Harsha, Mrinal Kumar, Ramprasad Saptharishi

Understanding the limits of list-decodability of Reed-Solomon codes has been one of the most important open problems in algebraic coding theory. Recently, Brakensiek, Chen, Putterman, Zhang, and Zheng, in a remarkable breakthrough, showed that Reed-Solomon (RS) codes over fields of large characteristic are algorithmically list-decodable all the way up to capacity. Building on this result, Jeronimo subsequently extended these techniques to solve the proximity-gaps question for RS codes. In this article, we give a unified and transparent exposition of these results.

Authors: Prahladh Harsha, Mrinal Kumar, Ramprasad Saptharishi

Understanding the limits of list-decodability of Reed-Solomon codes has been one of the most important open problems in algebraic coding theory. Recently, Brakensiek, Chen, Putterman, Zhang, and Zheng, in a remarkable breakthrough, showed that Reed-Solomon (RS) codes over fields of large characteristic are algorithmically list-decodable all the way up to capacity. Building on this result, Jeronimo subsequently extended these techniques to solve the proximity-gaps question for RS codes. In this article, we give a unified and transparent exposition of these results.

Wednesday, October 07 2026, 00:00

Simple Extremely Lossy Functions from Small-Exponent Hashing

Authors: Damiano Abram, Agni Datta, Archisman Dutta, Lawrence Roy

Extremely Lossy Functions (ELFs) are a standard model primitive that captures many useful properties of random oracles (Zhandry, Crypto 2016). While there are many variations of ELFs with additional properties, every construction (excluding obfuscation) has followed essentially the same template of bootstrapping from a sequence of ELFs secure only against fixed-size adversaries, and every construction was based on only the exponential hardness of DDH (or $k$-Lin), an assumption that is only reasonable over elliptic curves. We introduce and construct Extremely Lossy Trapdoor Hashing (ELTDH), a stronger notion that implies all known variations of ELFs. Our construction achieves ELTDH in one go, without bootstrapping from schemes secure for only fixed-size adversaries, which makes it simpler and more efficient than existing ELFs. We assume exponential security of the small-exponent discrete logarithm, together with polynomial security of decisional composite residuosity (DCR). Exponential security is only required in the size of the secret exponent, not the size of the group, so the assumption plausibly holds for multiplication modulo $N^2$ (and for many other cryptographic groups), despite the subexponential-time discrete logarithm attacks from index calculus. Our results diversify the assumptions underlying ELFs, while also giving a simpler construction.

Authors: Damiano Abram, Agni Datta, Archisman Dutta, Lawrence Roy

Extremely Lossy Functions (ELFs) are a standard model primitive that captures many useful properties of random oracles (Zhandry, Crypto 2016). While there are many variations of ELFs with additional properties, every construction (excluding obfuscation) has followed essentially the same template of bootstrapping from a sequence of ELFs secure only against fixed-size adversaries, and every construction was based on only the exponential hardness of DDH (or $k$-Lin), an assumption that is only reasonable over elliptic curves. We introduce and construct Extremely Lossy Trapdoor Hashing (ELTDH), a stronger notion that implies all known variations of ELFs. Our construction achieves ELTDH in one go, without bootstrapping from schemes secure for only fixed-size adversaries, which makes it simpler and more efficient than existing ELFs. We assume exponential security of the small-exponent discrete logarithm, together with polynomial security of decisional composite residuosity (DCR). Exponential security is only required in the size of the secret exponent, not the size of the group, so the assumption plausibly holds for multiplication modulo $N^2$ (and for many other cryptographic groups), despite the subexponential-time discrete logarithm attacks from index calculus. Our results diversify the assumptions underlying ELFs, while also giving a simpler construction.

Wednesday, October 07 2026, 00:00

Tight Bounds for Tusnády's Problem in the Plane

Authors: Zhewei Wei

We show that the worst-case combinatorial discrepancy of $n$ points in the plane with respect to axis-parallel rectangles is $Θ(\log^{3/2}n)$. The known bounds were $Ω(\log n)$ and $O(\log^{3/2}n)$; we prove the matching lower bound. It holds for random point sets: for every $A>0$, there is a constant $c_A>0$ such that, with probability at least $1-e^{-An}$, every coloring of $n$ independent uniform points in the unit square has an anchored rectangle with imbalance at least $c_A(\log_2n)^{3/2}$. The proof is surprisingly simple and elementary. It reveals one coordinate digit by digit. With overwhelming probability over the points, the conditional gains of an oscillation potential add up to $Ω(\log^{3/2}n)$ over $Θ(\log n)$ digits. Bounded differences control the fluctuations well enough for a union bound over all colorings.

Authors: Zhewei Wei

We show that the worst-case combinatorial discrepancy of $n$ points in the plane with respect to axis-parallel rectangles is $Θ(\log^{3/2}n)$. The known bounds were $Ω(\log n)$ and $O(\log^{3/2}n)$; we prove the matching lower bound. It holds for random point sets: for every $A>0$, there is a constant $c_A>0$ such that, with probability at least $1-e^{-An}$, every coloring of $n$ independent uniform points in the unit square has an anchored rectangle with imbalance at least $c_A(\log_2n)^{3/2}$. The proof is surprisingly simple and elementary. It reveals one coordinate digit by digit. With overwhelming probability over the points, the conditional gains of an oscillation potential add up to $Ω(\log^{3/2}n)$ over $Θ(\log n)$ digits. Bounded differences control the fluctuations well enough for a union bound over all colorings.

Wednesday, October 07 2026, 00:00

Simulated Annealing for Antenna Placements

Authors: Mikkel Abrahamsen, Jacobus Conradi, Asbjørn Lind

The 2026 ACM SIGSPATIAL GIS Cup posed the following geometric challenge: Given a set of simple, pair-wise disjoint polygons, compute $k$ antennas (points) on polygon boundaries, maximizing the number of polygons with at least a fraction $τ$ of their perimeter visible from the antennas. Contestants had 24 hours to produce the best possible solutions. We describe an approach that separates geometric visibility preprocessing from a portfolio of incremental combinatorial searches. A construction pool provides initial solutions with antennas restricted to polygon vertices; simulated annealing explores one-for-one antenna swaps, complemented by exact discrete one-swap descent, ruin-and-recreate, and elite crossover. A secondary objective rewards progress toward the service threshold without overriding the primary score. Candidate antennas are later expanded to include points in polygon-edge interiors. Our submitted solutions cover between 261 and 16,273 buildings across the nine parameter combinations, and the team was invited to present as one of the top entries. The code is available at github.com/JacobusTheSecond/giscup.

Authors: Mikkel Abrahamsen, Jacobus Conradi, Asbjørn Lind

The 2026 ACM SIGSPATIAL GIS Cup posed the following geometric challenge: Given a set of simple, pair-wise disjoint polygons, compute $k$ antennas (points) on polygon boundaries, maximizing the number of polygons with at least a fraction $τ$ of their perimeter visible from the antennas. Contestants had 24 hours to produce the best possible solutions. We describe an approach that separates geometric visibility preprocessing from a portfolio of incremental combinatorial searches. A construction pool provides initial solutions with antennas restricted to polygon vertices; simulated annealing explores one-for-one antenna swaps, complemented by exact discrete one-swap descent, ruin-and-recreate, and elite crossover. A secondary objective rewards progress toward the service threshold without overriding the primary score. Candidate antennas are later expanded to include points in polygon-edge interiors. Our submitted solutions cover between 261 and 16,273 buildings across the nine parameter combinations, and the team was invited to present as one of the top entries. The code is available at https://github.com/JacobusTheSecond/giscup.

Wednesday, October 07 2026, 00:00

Exposition of an approximation algorithm for mixed volumes of a constant number of convex bodies

Authors: Hariharan Narayanan

We study $\varepsilon$-relative approximation of mixed volumes of a fixed number $k$ of full-dimensional convex bodies in $\mathbb{R}^n$, given membership oracles and a known bound $B_n\subseteq K_i\subseteq R_0B_n$. We present a randomized algorithm that estimates any prescribed mixed volume within relative error $\varepsilon$ with probability at least $1-δ$, using polynomially many oracle calls and bit operations in $n$, $\log R_0$, $\varepsilon^{-1}$, and $\logδ^{-1}$ for fixed $k$.

Authors: Hariharan Narayanan

We study $\varepsilon$-relative approximation of mixed volumes of a fixed number $k$ of full-dimensional convex bodies in $\mathbb{R}^n$, given membership oracles and a known bound $B_n\subseteq K_i\subseteq R_0B_n$. We present a randomized algorithm that estimates any prescribed mixed volume within relative error $\varepsilon$ with probability at least $1-δ$, using polynomially many oracle calls and bit operations in $n$, $\log R_0$, $\varepsilon^{-1}$, and $\logδ^{-1}$ for fixed $k$.

Wednesday, October 07 2026, 00:00

Cores Characterize the One-Pass Streaming Complexity of CSPs

Authors: Joshua Brakensiek, Aaron Putterman, Amatya Sharma, Santhoshini Velusamy

We study the one-pass streaming complexity of CSPs over a fixed finite relation $R$ under three natural objectives: $\textsf{SAT}(R)$, deciding whether all constraints can be satisfied; $\textsf{Min}$-$\textsf{CSP}(R)$, approximately minimizing the number of unsatisfied constraints; and $\textsf{Exact-CSP}(R)$, exactly computing the maximum number of satisfied constraints. Sharma and Velusamy (ESA 2026) characterized the streaming complexity of satisfiability for CSPs with literals using the non-redundancy parameter $\textsf{NRD}_n(R)$, which roughly measures the largest instance in which every constraint is independently necessary. For the most general setting without literals, they obtained the corresponding characterization for Boolean relations and showed obstacles to extending their techniques to larger domains. Kol, Paramonov, Saxena, and Yu (ITCS 2023) similarly characterized the streaming complexity of $\textsf{Exact-CSP}(R)$ for Boolean CSPs with literals in terms of the degree deg$(R)$ of the relation when written as a polynomial, while without literals, the corresponding result was known only for $\textsf{Max-Cut}$. For all three of the objectives we study, we give tight characterizations for unweighted CSP instances over arbitrary finite domains. The streaming algorithms we provide are deterministic, while the corresponding bounds are tight up to polylogarithmic factors, even against randomized algorithms. The central idea in all three results is a reduction of $R$ to its core, a canonical subrelation of $R$ which admits gadgets that allow for the hard-pinning (or fixing) of variables.

Authors: Joshua Brakensiek, Aaron Putterman, Amatya Sharma, Santhoshini Velusamy

We study the one-pass streaming complexity of CSPs over a fixed finite relation $R$ under three natural objectives: $\textsf{SAT}(R)$, deciding whether all constraints can be satisfied; $\textsf{Min}$-$\textsf{CSP}(R)$, approximately minimizing the number of unsatisfied constraints; and $\textsf{Exact-CSP}(R)$, exactly computing the maximum number of satisfied constraints. Sharma and Velusamy (ESA 2026) characterized the streaming complexity of satisfiability for CSPs with literals using the non-redundancy parameter $\textsf{NRD}_n(R)$, which roughly measures the largest instance in which every constraint is independently necessary. For the most general setting without literals, they obtained the corresponding characterization for Boolean relations and showed obstacles to extending their techniques to larger domains. Kol, Paramonov, Saxena, and Yu (ITCS 2023) similarly characterized the streaming complexity of $\textsf{Exact-CSP}(R)$ for Boolean CSPs with literals in terms of the degree deg$(R)$ of the relation when written as a polynomial, while without literals, the corresponding result was known only for $\textsf{Max-Cut}$. For all three of the objectives we study, we give tight characterizations for unweighted CSP instances over arbitrary finite domains. The streaming algorithms we provide are deterministic, while the corresponding bounds are tight up to polylogarithmic factors, even against randomized algorithms. The central idea in all three results is a reduction of $R$ to its core, a canonical subrelation of $R$ which admits gadgets that allow for the hard-pinning (or fixing) of variables.

Wednesday, October 07 2026, 00:00

Almost Instance Optimal Sum and Moment Estimation Using Weighted Sampling

Authors: Anup Bhattacharya, Suryendu Mondal, Pinki Pradhan

We design an almost instance optimal algorithm for the sum estimation problem using weighted sampling. We show that the sample complexity for sum estimation is closely related to the $\ell_2$ norm of the weighted sampling distribution. We show an almost instance optimal lower bound for this problem as well. We also study the moment estimation problem and design an algorithm that has better instance-wise sample complexity bounds.

Authors: Anup Bhattacharya, Suryendu Mondal, Pinki Pradhan

We design an almost instance optimal algorithm for the sum estimation problem using weighted sampling. We show that the sample complexity for sum estimation is closely related to the $\ell_2$ norm of the weighted sampling distribution. We show an almost instance optimal lower bound for this problem as well. We also study the moment estimation problem and design an algorithm that has better instance-wise sample complexity bounds.

Wednesday, October 07 2026, 00:00

When Can Stateless Recovery Defeat Byzantine Quorum Safety? A Tight Normal Form for Single-Step BFT

Authors: Arnab Mallick, Indraveni Chebolu

Byzantine quorum safety relies on correct replicas refusing to sign conflicting values. A replica that loses its protocol state during recovery but retains its identity and signing key may forget an earlier vote. We study certificates formed by matching signed votes from at least $q$ of $n$ replicas, assuming that each correct replica avoids conflicting votes between recoveries. If two conflicting certificates form, their overlap has size between $2q-n$ and $b+c$, where $b$ counts Byzantine replicas and $c$ counts correct identities that recovered during the execution considered. Our main result decomposes the slack $b+c-(2q-n)$ into four nonnegative counts: extra signers in the first certificate, extra signers in the second, identities in neither certificate, and Byzantine or recovering identities outside their overlap. Zero slack forces an exact signer partition. With $n=3f+1$ replicas, threshold $q=2f+1$, at most $f$ Byzantine replicas, and exactly one correct recovery event, any conflicting pair forces exactly $f$ Byzantine replicas, all in the overlap together with the recovered replica; each certificate has a disjoint side of $f$ correct replicas. A minimal protocol attains this form. We distinguish certificate formation from acceptance, give a sufficient check using configured fault and recovery caps, and explain why durable vote records written before signature release prevent the conflict.

Authors: Arnab Mallick, Indraveni Chebolu

Byzantine quorum safety relies on correct replicas refusing to sign conflicting values. A replica that loses its protocol state during recovery but retains its identity and signing key may forget an earlier vote. We study certificates formed by matching signed votes from at least $q$ of $n$ replicas, assuming that each correct replica avoids conflicting votes between recoveries. If two conflicting certificates form, their overlap has size between $2q-n$ and $b+c$, where $b$ counts Byzantine replicas and $c$ counts correct identities that recovered during the execution considered. Our main result decomposes the slack $b+c-(2q-n)$ into four nonnegative counts: extra signers in the first certificate, extra signers in the second, identities in neither certificate, and Byzantine or recovering identities outside their overlap. Zero slack forces an exact signer partition. With $n=3f+1$ replicas, threshold $q=2f+1$, at most $f$ Byzantine replicas, and exactly one correct recovery event, any conflicting pair forces exactly $f$ Byzantine replicas, all in the overlap together with the recovered replica; each certificate has a disjoint side of $f$ correct replicas. A minimal protocol attains this form. We distinguish certificate formation from acceptance, give a sufficient check using configured fault and recovery caps, and explain why durable vote records written before signature release prevent the conflict.

Wednesday, October 07 2026, 00:00

How to Fix a Broken Metric: A Linear Kernel, Tight Bounds, and Tree Metrics

Authors: Sayan Bandyapadhyay, William Lochet, Daniel Lokshtanov, Saket Saurabh, Chinmay Sonar, Vaishali Surianarayanan, Jie Xue

Given a complete graph whose edge weights represent dissimilarities, Metric Violation Distance asks whether at most $k$ weights can be changed to form a metric. Motivated by metric repair for noisy data, the problem admits a polynomial-time $O(\log n)$-approximation due to Cohen-Addad, Fan, Lee and de Mesmay [SIAM J. Comput., 2025]. In the context of parameterized complexity, Fan, Gilbert, Raichel, Sonthalia and Van Buskirk [SWAT 2020] gave a $k^{O(k)}n^{O(1)}$-time algorithm. Fomin, Golovach and More [IPEC 2026] obtained an $O(k^2)$ kernel and a single-exponential algorithm for the ultrametric case. They asked whether general metrics admit a single-exponential algorithm and a polynomial kernel, and whether the tree-metric analogue is fixed-parameter tractable. We answer all three questions. We give a $2^{O(k)}n^{O(1)}$-time algorithm and prove that, unless ETH fails, no $2^{o(k)}n^{O(1)}$-time algorithm exists, even when all input distances lie in $\{1,2,3\}$. We also give a kernel with at most $6k$ vertices. The kernel supports solution lifting and can precede any approximation algorithm. Combined with the $O(\log n)$-approximation of Cohen-Addad, Fan, Lee and de Mesmay, it yields an $O(\log \mathrm{OPT})$-approximation at no asymptotic cost in running time. Both results extend to an interval generalization in which each edge $e$ has an observed value $M_e$ and an admissible range $[A_e,B_e]$ within which it may be reassigned; the kernel then has $7k$ vertices. Finally, Tree Metric Violation Distance is fixed-parameter tractable and solvable in $k^{O(k)}n^{O(1)}$ time.

Authors: Sayan Bandyapadhyay, William Lochet, Daniel Lokshtanov, Saket Saurabh, Chinmay Sonar, Vaishali Surianarayanan, Jie Xue

Given a complete graph whose edge weights represent dissimilarities, Metric Violation Distance asks whether at most $k$ weights can be changed to form a metric. Motivated by metric repair for noisy data, the problem admits a polynomial-time $O(\log n)$-approximation due to Cohen-Addad, Fan, Lee and de Mesmay [SIAM J. Comput., 2025]. In the context of parameterized complexity, Fan, Gilbert, Raichel, Sonthalia and Van Buskirk [SWAT 2020] gave a $k^{O(k)}n^{O(1)}$-time algorithm. Fomin, Golovach and More [IPEC 2026] obtained an $O(k^2)$ kernel and a single-exponential algorithm for the ultrametric case. They asked whether general metrics admit a single-exponential algorithm and a polynomial kernel, and whether the tree-metric analogue is fixed-parameter tractable. We answer all three questions. We give a $2^{O(k)}n^{O(1)}$-time algorithm and prove that, unless ETH fails, no $2^{o(k)}n^{O(1)}$-time algorithm exists, even when all input distances lie in $\{1,2,3\}$. We also give a kernel with at most $6k$ vertices. The kernel supports solution lifting and can precede any approximation algorithm. Combined with the $O(\log n)$-approximation of Cohen-Addad, Fan, Lee and de Mesmay, it yields an $O(\log \mathrm{OPT})$-approximation at no asymptotic cost in running time. Both results extend to an interval generalization in which each edge $e$ has an observed value $M_e$ and an admissible range $[A_e,B_e]$ within which it may be reassigned; the kernel then has $7k$ vertices. Finally, Tree Metric Violation Distance is fixed-parameter tractable and solvable in $k^{O(k)}n^{O(1)}$ time.

Wednesday, October 07 2026, 00:00

Explicit Asymptotic Bounds for Sequential Calibration Beyond $T^{2/3}$

Authors: Eric Dai, Maxwell Fishelson

Probability forecasts are calibrated when predicted probabilities match empirical outcome frequencies: among events assigned a probability $p$, we'd hope that the fraction of positive outcomes is close to $p$. We study the problem of sequential forecasting of binary outcomes. The classical $O(T^{2/3})$ bound on expected cumulative $\ell_1$-calibration error established by Foster and Vohra stood for over two decades until Dagan et al. reduced the exponent $2/3$ by an unspecified constant. We establish a new two-phase recursive labeling strategy for the sign-preservation-with-reuse game that yields the bound $O(n^αt^β)$ for all choices of space and time. We then sharpen the reduction from upper bounds on sign preservation to calibration by modifying the equivalence of Dagan et al. to use only $O(\log T)$ instances of the sign-preservation-with-reuse game. This lets us establish an explicit bound of $O(T^{0.662942288})$, the first explicit exponent below $2/3$ for sequential calibration, by combining both improvements and choosing explicit feasible parameters.

Authors: Eric Dai, Maxwell Fishelson

Probability forecasts are calibrated when predicted probabilities match empirical outcome frequencies: among events assigned a probability $p$, we'd hope that the fraction of positive outcomes is close to $p$. We study the problem of sequential forecasting of binary outcomes. The classical $O(T^{2/3})$ bound on expected cumulative $\ell_1$-calibration error established by Foster and Vohra stood for over two decades until Dagan et al. reduced the exponent $2/3$ by an unspecified constant. We establish a new two-phase recursive labeling strategy for the sign-preservation-with-reuse game that yields the bound $O(n^αt^β)$ for all choices of space and time. We then sharpen the reduction from upper bounds on sign preservation to calibration by modifying the equivalence of Dagan et al. to use only $O(\log T)$ instances of the sign-preservation-with-reuse game. This lets us establish an explicit bound of $O(T^{0.662942288})$, the first explicit exponent below $2/3$ for sequential calibration, by combining both improvements and choosing explicit feasible parameters.

Wednesday, October 07 2026, 00:00

Almost-Linear Decremental Single-Source Distance Estimates in Directed Graphs via Cut Balance

Authors: Hanqing Li

We give a deterministic reduction for maintaining simultaneous approximate single-source distance estimates in online decremental directed graphs. For positive integer weights in $[1,W]$, the algorithm maintains an explicit array of integer $(1+\varepsilon)$ upper estimates, identifies unreachable vertices exactly, and answers numerical queries in constant time. Let $N=m+n$, $S=N+\lceil1/\varepsilon\rceil$, and assume $\log W=\operatorname{polylog}(S)$. Initialization and all updates take $O(Δ)+(N+Δ_{\mathrm{eff}}+\mathcal{L}/\varepsilon)S^{o(1)}$ time, where $Δ$ counts raw updates, $Δ_{\mathrm{eff}}=O(m(1+\log W)/\varepsilon)$ counts filtered updates, and $\mathcal{L}$ measures finite distance growth weighted by the current indegrees of the reachable subgraph. Removed edges and vertices that become unreachable incur no subsequent growth charge. Consequently, the worst-case bound is $O(Δ)+(N/\varepsilon)S^{o(1)}$, which is almost linear for subpolynomial inverse accuracy. The reduction uses the dynamic minimum-ratio cut and exact reachability algorithms of van den Brand et al. (FOCS 2024). A degree-weighted clipped logarithmic potential turns constant relative cut balance into accuracy at every target; a successor cut then restores strict feasibility. A distance warm start and the energy released by decreasing return coefficients yield the refined growth bound. Return mass also amplifies the accuracy of the existing change detector. The public estimates can be monotone, with $O(n+\mathcal{J}/\varepsilon)$ array writes for an unweighted finite-growth measure $\mathcal{J}\le\mathcal{L}$. Execution uses rational arithmetic. A separate reduction extends the worst-case guarantee to nonnegative integer weights. The algorithm maintains numerical estimates and does not provide fast path reporting.

Authors: Hanqing Li

We give a deterministic reduction for maintaining simultaneous approximate single-source distance estimates in online decremental directed graphs. For positive integer weights in $[1,W]$, the algorithm maintains an explicit array of integer $(1+\varepsilon)$ upper estimates, identifies unreachable vertices exactly, and answers numerical queries in constant time. Let $N=m+n$, $S=N+\lceil1/\varepsilon\rceil$, and assume $\log W=\operatorname{polylog}(S)$. Initialization and all updates take $O(Δ)+(N+Δ_{\mathrm{eff}}+\mathcal{L}/\varepsilon)S^{o(1)}$ time, where $Δ$ counts raw updates, $Δ_{\mathrm{eff}}=O(m(1+\log W)/\varepsilon)$ counts filtered updates, and $\mathcal{L}$ measures finite distance growth weighted by the current indegrees of the reachable subgraph. Removed edges and vertices that become unreachable incur no subsequent growth charge. Consequently, the worst-case bound is $O(Δ)+(N/\varepsilon)S^{o(1)}$, which is almost linear for subpolynomial inverse accuracy. The reduction uses the dynamic minimum-ratio cut and exact reachability algorithms of van den Brand et al. (FOCS 2024). A degree-weighted clipped logarithmic potential turns constant relative cut balance into accuracy at every target; a successor cut then restores strict feasibility. A distance warm start and the energy released by decreasing return coefficients yield the refined growth bound. Return mass also amplifies the accuracy of the existing change detector. The public estimates can be monotone, with $O(n+\mathcal{J}/\varepsilon)$ array writes for an unweighted finite-growth measure $\mathcal{J}\le\mathcal{L}$. Execution uses rational arithmetic. A separate reduction extends the worst-case guarantee to nonnegative integer weights. The algorithm maintains numerical estimates and does not provide fast path reporting.

Wednesday, October 07 2026, 00:00

A Tardos-Type Algorithm for Separable Convex Quadratic Programming

Authors: Hanqing Li

We give an exact algorithm for continuous separable convex quadratic programming with an integer equality matrix and nonnegative variables. The number of rational arithmetic operations and comparisons is polynomial in the dimensions and the encoding length of the constraint matrix, independently of the right-hand side, linear costs, and all nonnegative quadratic weights. Intermediate rational encodings are polynomial in the complete input. This yields a strongly polynomial algorithm for every integer matrix class with polynomially bounded entry encodings, including arbitrary matrices with entries in $\{0,\pm1\}$. The local solver compresses a quadratic objective on an integer box and solves only the compressed continuous problem. Two-sided proximity on boxes with rational bounds transfers its solution to a nearby original optimum; integer optima are used only in the proof. A single linear program supplies an error bound and a dual potential, while tight-coordinate revelation and fixed feasible anchors ensure termination and control encoding lengths. An explicit lifting extends the result to convex piecewise quadratic functions of signed integer affine features, with operation counts independent of breakpoints and objective coefficients. Applications include continuous multicommodity flow with shared capacities and piecewise quadratic costs of aggregate congestion.

Authors: Hanqing Li

We give an exact algorithm for continuous separable convex quadratic programming with an integer equality matrix and nonnegative variables. The number of rational arithmetic operations and comparisons is polynomial in the dimensions and the encoding length of the constraint matrix, independently of the right-hand side, linear costs, and all nonnegative quadratic weights. Intermediate rational encodings are polynomial in the complete input. This yields a strongly polynomial algorithm for every integer matrix class with polynomially bounded entry encodings, including arbitrary matrices with entries in $\{0,\pm1\}$. The local solver compresses a quadratic objective on an integer box and solves only the compressed continuous problem. Two-sided proximity on boxes with rational bounds transfers its solution to a nearby original optimum; integer optima are used only in the proof. A single linear program supplies an error bound and a dual potential, while tight-coordinate revelation and fixed feasible anchors ensure termination and control encoding lengths. An explicit lifting extends the result to convex piecewise quadratic functions of signed integer affine features, with operation counts independent of breakpoints and objective coefficients. Applications include continuous multicommodity flow with shared capacities and piecewise quadratic costs of aggregate congestion.

Wednesday, October 07 2026, 00:00

Stronger Hardness for Submodular Maximization Subject to a Matroid Constraint

Authors: Moran Feldman, Alan Kuhnle

Maximizing a submodular function subject to a matroid constraint is a cornerstone problem in combinatorial optimization. The state-of-the-art algorithm for this problem obtains $0.401$-approximation~\cite{buchbinder2024constrained}, and the state-of-the-art hardness result shows that no polynomial time algorithm can obtain better than $0.478$-approximation for this problem~\cite{oveisgharan2011submodular}. In this work, we present the first improvement in $15$ years for the hardness result, showing that no polynomial time algorithm in the value-oracle model can obtain better than $8/17 \approx 0.471$-approximation, even for the special case of a cardinality or (simplified) partition matroid constraint.

Authors: Moran Feldman, Alan Kuhnle

Maximizing a submodular function subject to a matroid constraint is a cornerstone problem in combinatorial optimization. The state-of-the-art algorithm for this problem obtains $0.401$-approximation~\cite{buchbinder2024constrained}, and the state-of-the-art hardness result shows that no polynomial time algorithm can obtain better than $0.478$-approximation for this problem~\cite{oveisgharan2011submodular}. In this work, we present the first improvement in $15$ years for the hardness result, showing that no polynomial time algorithm in the value-oracle model can obtain better than $8/17 \approx 0.471$-approximation, even for the special case of a cardinality or (simplified) partition matroid constraint.

Wednesday, October 07 2026, 00:00

Byzantine-Tolerant Causal Unicast with Constant Message Space Overhead

Authors: Purv Patel, Ajay D. Kshemkalyani

Causal message ordering provides essential semantics for distributed applications, yet ensuring it within an asynchronous system subject to Byzantine failures presents fundamental theoretical and practical challenges. Prior research establishes that algorithms cannot guarantee both strong safety and liveness without using cryptography under these conditions. Existing Byzantine-tolerant solutions make synchrony assumptions or suffer from $O(n)$ message space overheads and $O(n^2)$ message complexity, where $n$ is the number of processes in the system, or use cryptography, but may not guarantee strong safety. In this paper, we present a novel Byzantine-tolerant causal ordering algorithm that achieves an optimal $O(1)$ application message space overhead for point-to-point messages. Our approach uses a Sender Permission to Send (SPS) invariant and an \textit{Isolated-Buffer Optimistic Model} for the memory management architecture. To circumvent Byzantine state-pinning and head-of-line blocking attacks, instead of unified causal buffers, we use isolated, per-peer queues equipped with event-driven \textit{Cascading Space Evictions}. We formally prove that our algorithm guarantees system-wide liveness and satisfies a weakened causal safety abstraction called \textit{Congestion-Relaxed Causal Delivery}. Under this model, weak causal safety is strictly preserved for all honest-to-honest communications unless extreme network latency or Byzantine withholding attacks exceed quantifiable local buffer capacities, forcing optimistic queue evictions. This formal guarantee successfully balances causal ordering with high throughput, constant message space overhead, low computational overhead, and strictly bounded local space.

Authors: Purv Patel, Ajay D. Kshemkalyani

Causal message ordering provides essential semantics for distributed applications, yet ensuring it within an asynchronous system subject to Byzantine failures presents fundamental theoretical and practical challenges. Prior research establishes that algorithms cannot guarantee both strong safety and liveness without using cryptography under these conditions. Existing Byzantine-tolerant solutions make synchrony assumptions or suffer from $O(n)$ message space overheads and $O(n^2)$ message complexity, where $n$ is the number of processes in the system, or use cryptography, but may not guarantee strong safety. In this paper, we present a novel Byzantine-tolerant causal ordering algorithm that achieves an optimal $O(1)$ application message space overhead for point-to-point messages. Our approach uses a Sender Permission to Send (SPS) invariant and an \textit{Isolated-Buffer Optimistic Model} for the memory management architecture. To circumvent Byzantine state-pinning and head-of-line blocking attacks, instead of unified causal buffers, we use isolated, per-peer queues equipped with event-driven \textit{Cascading Space Evictions}. We formally prove that our algorithm guarantees system-wide liveness and satisfies a weakened causal safety abstraction called \textit{Congestion-Relaxed Causal Delivery}. Under this model, weak causal safety is strictly preserved for all honest-to-honest communications unless extreme network latency or Byzantine withholding attacks exceed quantifiable local buffer capacities, forcing optimistic queue evictions. This formal guarantee successfully balances causal ordering with high throughput, constant message space overhead, low computational overhead, and strictly bounded local space.

Wednesday, October 07 2026, 00:00

Trading with the STARS: Algorithm Design & Spectrum of Fundamental Limits for Trading with Storage

Authors: Jerry Anunrojwong, Akshit Kumar, Rachitesh Kumar

We study an online trading problem where a trader, given a sequence of i.i.d. prices drawn from a known distribution $F$ on $[0,1]$, must make irrevocable buy, sell, or hold decisions subject to storage constraints. We investigate achievable algorithmic performance measured in terms of regret, the difference between the expected profit of the hindsight optimal policy that knows the entire price sequence and an online algorithm. We analyze finite atomic and continuous distributions characterized by their local behavior around the median which we capture using a parameter $β$. The parameter $β$ quantifies how the mass of prices accumulates around the distribution median. We identify a new driver of algorithmic performance, demonstrating that median gaps coupled with an initial inventory level of zero can force regret scaling of $Ω(T^{(β+ 1)/(2β+4)})$ --- establishing a novel spectrum of fundamental limits on algorithmic performance. We then study STARS, short for Storage Trading by Averaging Repeatedly across multiple Scenarios, which simulates possible future price scenarios to approximate the value-to-go function and make buy/sell/hold decisions. We show that STARS obtain near-optimal algorithmic performance (upto poly-logarithmic factors) across a broad range of distributions. In particular, it achieves $O(\log T)$ regret for finite atomic prices, $\widetilde{O}(T^{β/(2β+2)})$ for continuous distributions without a median gap and $\widetilde{O}(T^{(β+1)/(2β+4)})$ for continuous distributions with a median gap for $β\geq 0$.

Authors: Jerry Anunrojwong, Akshit Kumar, Rachitesh Kumar

We study an online trading problem where a trader, given a sequence of i.i.d. prices drawn from a known distribution $F$ on $[0,1]$, must make irrevocable buy, sell, or hold decisions subject to storage constraints. We investigate achievable algorithmic performance measured in terms of regret, the difference between the expected profit of the hindsight optimal policy that knows the entire price sequence and an online algorithm. We analyze finite atomic and continuous distributions characterized by their local behavior around the median which we capture using a parameter $β$. The parameter $β$ quantifies how the mass of prices accumulates around the distribution median. We identify a new driver of algorithmic performance, demonstrating that median gaps coupled with an initial inventory level of zero can force regret scaling of $Ω(T^{(β+ 1)/(2β+4)})$ --- establishing a novel spectrum of fundamental limits on algorithmic performance. We then study STARS, short for Storage Trading by Averaging Repeatedly across multiple Scenarios, which simulates possible future price scenarios to approximate the value-to-go function and make buy/sell/hold decisions. We show that STARS obtain near-optimal algorithmic performance (upto poly-logarithmic factors) across a broad range of distributions. In particular, it achieves $O(\log T)$ regret for finite atomic prices, $\widetilde{O}(T^{β/(2β+2)})$ for continuous distributions without a median gap and $\widetilde{O}(T^{(β+1)/(2β+4)})$ for continuous distributions with a median gap for $β\geq 0$.

Wednesday, October 07 2026, 00:00

A Fast Algorithm for Maltsev Constraints

Authors: Victor Lagerkvist

The constraint satisfaction problem over a set of relations $Γ$ (CSP($Γ$)) is the computational problem of deciding if a set of constraints admits at least one solution. The classical complexity for finite-domain CSP($Γ$) is settled by the CSP dichotomy theorem: it is tractable if $Γ$ satisfies a non-trivial algebraic invariant and is NP-complete otherwise. However, not all these algebraic invariants result in efficient algorithms despite being theoretically tractable. A notable case that generalizes linear equations is that of Maltsev CSPs: an $n$-variable instance with $m$ constraints is solvable in roughly $O(n^8 \cdot m)$ time by Bulatov and Dalmau (SIAM J. Comput. 2006) or $O(n^4 \cdot m)$ time by Dyer and Richerby (SIAM J. Comput. 2013). At the same time, arguably, most "natural" and efficiently usable polynomial-time algorithms rarely exceed a quadratic or cubic time bound. In this paper we revisit Maltsev constraints with this question in mind and find a $O(n^2 \cdot m)$ algorithm (for finite languages, for infinite languages we in addition need to take the total size of the instance into account). The main novel idea is to not attempt to improve the bottleneck in Bulatov and Dalmau (the Fix-Values procedure) but to avoid it altogether with a slightly more refined approach that allows us to search through a smaller space.

Authors: Victor Lagerkvist

The constraint satisfaction problem over a set of relations $Γ$ (CSP($Γ$)) is the computational problem of deciding if a set of constraints admits at least one solution. The classical complexity for finite-domain CSP($Γ$) is settled by the CSP dichotomy theorem: it is tractable if $Γ$ satisfies a non-trivial algebraic invariant and is NP-complete otherwise. However, not all these algebraic invariants result in efficient algorithms despite being theoretically tractable. A notable case that generalizes linear equations is that of Maltsev CSPs: an $n$-variable instance with $m$ constraints is solvable in roughly $O(n^8 \cdot m)$ time by Bulatov and Dalmau (SIAM J. Comput. 2006) or $O(n^4 \cdot m)$ time by Dyer and Richerby (SIAM J. Comput. 2013). At the same time, arguably, most "natural" and efficiently usable polynomial-time algorithms rarely exceed a quadratic or cubic time bound. In this paper we revisit Maltsev constraints with this question in mind and find a $O(n^2 \cdot m)$ algorithm (for finite languages, for infinite languages we in addition need to take the total size of the instance into account). The main novel idea is to not attempt to improve the bottleneck in Bulatov and Dalmau (the Fix-Values procedure) but to avoid it altogether with a slightly more refined approach that allows us to search through a smaller space.

Wednesday, October 07 2026, 00:00

Optimal and Efficient Online Inverse Optimization

Authors: Anupam Gupta, Guru Guruganesh, Honghao Lin, Vahab Mirrokni, Renato Paes Leme, David P. Woodruff

In online inverse linear optimization, a learner recommends an action and then observes the choice of an expert who maximizes a fixed, unknown linear objective on $\mathbb{R}^{d}$; the goal is to learn to optimize this objective without observing it. Sakaue recently obtained the optimal regret $O(\sqrt d)$ with a randomized algorithm making $(dT)^{O(d)}$ linear optimizations per round, and asked whether it can be attained in polynomial time. We answer positively: our deterministic algorithm has regret $O(\sqrt d)$ for every horizon $T$ and runs in time polynomial in $d$ and $T$. It is a variant of the variable-metric algorithms of Sakaue et al.\ and Cai et al., in which a metric update is revoked once the query point moves far enough from where the update was made.

Authors: Anupam Gupta, Guru Guruganesh, Honghao Lin, Vahab Mirrokni, Renato Paes Leme, David P. Woodruff

In online inverse linear optimization, a learner recommends an action and then observes the choice of an expert who maximizes a fixed, unknown linear objective on $\mathbb{R}^{d}$; the goal is to learn to optimize this objective without observing it. Sakaue recently obtained the optimal regret $O(\sqrt d)$ with a randomized algorithm making $(dT)^{O(d)}$ linear optimizations per round, and asked whether it can be attained in polynomial time. We answer positively: our deterministic algorithm has regret $O(\sqrt d)$ for every horizon $T$ and runs in time polynomial in $d$ and $T$. It is a variant of the variable-metric algorithms of Sakaue et al.\ and Cai et al., in which a metric update is revoked once the query point moves far enough from where the update was made.

Wednesday, October 07 2026, 00:00

Large Growth Happens: Gaussian Elimination with Partial Pivoting on Random Matrices

Authors: Daniel A. Spielman, Xifan Yu

We prove that the probability that Gaussian elimination with partial pivoting on $n \times n$ random matrices has growth $ρ$ is at least inverse quasi-polynomial: $Ω(\exp(-c \log^2 (ρ)\log(n)))$ for some constant $c > 0$. This lower bound breaks standard conjectures in the smoothed and average-case analysis of Gaussian elimination. To the best of our knowledge, it is the first non-trivial lower bound on the probability of large growth for Gaussian random matrices.

Authors: Daniel A. Spielman, Xifan Yu

We prove that the probability that Gaussian elimination with partial pivoting on $n \times n$ random matrices has growth $ρ$ is at least inverse quasi-polynomial: $Ω(\exp(-c \log^2 (ρ)\log(n)))$ for some constant $c > 0$. This lower bound breaks standard conjectures in the smoothed and average-case analysis of Gaussian elimination. To the best of our knowledge, it is the first non-trivial lower bound on the probability of large growth for Gaussian random matrices.

Wednesday, October 07 2026, 00:00

Parametrized Exact Hardware-Software Partitioning

Authors: Cameron Ibrahim, S M Ferdous, Erdal Mutlu, Ilya Safro, Mahantesh Halappanavar

When optimizing computing architecture for specific computationally intensive tasks, such as evaluating or training a neural network, it is important to identify what computational subtasks will offer the greatest decrease in cost (e.g., wall clock time or energy usage). This problem is known as Hardware-Software (HS) Partitioning, and it has a variety of formulations, many of which are NP-Hard. In this paper, we will define a family of HS Partitioning formulations which admit an exact fixed parameter tractable algorithm based on the directed pathwidth of the given task graph and show that this family of problems contains multiple existing formulations such as makespan minimization. Finally, we examine task graphs with small directed pathwidth that arise in real world applications and show that our algorithm can provide a speed up of up to 200x over a comparable linear programming approach utilizing the Gurobi ILP Library.

Authors: Cameron Ibrahim, S M Ferdous, Erdal Mutlu, Ilya Safro, Mahantesh Halappanavar

When optimizing computing architecture for specific computationally intensive tasks, such as evaluating or training a neural network, it is important to identify what computational subtasks will offer the greatest decrease in cost (e.g., wall clock time or energy usage). This problem is known as Hardware-Software (HS) Partitioning, and it has a variety of formulations, many of which are NP-Hard. In this paper, we will define a family of HS Partitioning formulations which admit an exact fixed parameter tractable algorithm based on the directed pathwidth of the given task graph and show that this family of problems contains multiple existing formulations such as makespan minimization. Finally, we examine task graphs with small directed pathwidth that arise in real world applications and show that our algorithm can provide a speed up of up to 200x over a comparable linear programming approach utilizing the Gurobi ILP Library.

Wednesday, October 07 2026, 00:00

Finite-Precision Gram-Schmidt Walks

Authors: Emile Anand, Jan van den Brand, Peter Chen

The Gram-Schmidt Walk is a randomized vector-balancing algorithm whose subgaussian guarantees support applications in discrepancy, experimental design, and data compression; however, these theoretical guarantees are established in exact arithmetic, whereas implementations must approximate least-squares directions, boundary updates, and sampling probabilities in finite precision. This is important because small numerical errors can change which coordinates freeze and thereby alter the subsequent trajectory. We analyze the concentration of the perturbed Gram-Schmidt walk directly under bounded, potentially biased and history-dependent errors. For $n$ input vectors of Euclidean norm at most one, we obtain a modified MGF bound depending on key error sources which recovers the original result as the error goes to zero. We also construct a full-column-rank instance in which bounded update errors produce bias of order $\min\{n^2\varepsilon,n\}$, showing that updates accumulate error unavoidably under this model. Finally, we validate our findings in a variety of settings by ablating on the bit precision and problem size.

Authors: Emile Anand, Jan van den Brand, Peter Chen

The Gram-Schmidt Walk is a randomized vector-balancing algorithm whose subgaussian guarantees support applications in discrepancy, experimental design, and data compression; however, these theoretical guarantees are established in exact arithmetic, whereas implementations must approximate least-squares directions, boundary updates, and sampling probabilities in finite precision. This is important because small numerical errors can change which coordinates freeze and thereby alter the subsequent trajectory. We analyze the concentration of the perturbed Gram-Schmidt walk directly under bounded, potentially biased and history-dependent errors. For $n$ input vectors of Euclidean norm at most one, we obtain a modified MGF bound depending on key error sources which recovers the original result as the error goes to zero. We also construct a full-column-rank instance in which bounded update errors produce bias of order $\min\{n^2\varepsilon,n\}$, showing that updates accumulate error unavoidably under this model. Finally, we validate our findings in a variety of settings by ablating on the bit precision and problem size.

Wednesday, October 07 2026, 00:00

Explicit tensors beyond the linear flattening barrier

Authors: Benjamin Lovitz

We construct explicit n x n x n tensors of border rank at least 3n-o(n), improving the previous record of (2 + $\varepsilon$)n due to (Landsberg and Michalek 2025). We also prove that the linear flattening method cannot be used to establish lower bounds on border rank beyond 2n-1. When n is odd, we prove that this bound is achieved by Koszul flattenings. When n is even, a result of (Landsberg 2015) shows that Koszul flattenings can achieve 2n-2, leaving an open gap of size one. Our 2n-1 bound improves the best known 6n-4 linear flattening barrier due to (Garg et al. 2019) and (Buczyński 2026). Combined, these results show that our 3n-o(n) construction, as well as the construction of Landsberg and Michalek, provide explicit examples of tensors with higher border rank than any linear flattening can achieve.

Authors: Benjamin Lovitz

We construct explicit n x n x n tensors of border rank at least 3n-o(n), improving the previous record of (2 + $\varepsilon$)n due to (Landsberg and Michalek 2025). We also prove that the linear flattening method cannot be used to establish lower bounds on border rank beyond 2n-1. When n is odd, we prove that this bound is achieved by Koszul flattenings. When n is even, a result of (Landsberg 2015) shows that Koszul flattenings can achieve 2n-2, leaving an open gap of size one. Our 2n-1 bound improves the best known 6n-4 linear flattening barrier due to (Garg et al. 2019) and (Buczyński 2026). Combined, these results show that our 3n-o(n) construction, as well as the construction of Landsberg and Michalek, provide explicit examples of tensors with higher border rank than any linear flattening can achieve.

Wednesday, October 07 2026, 00:00

Faster dynamic programming for tridiagonal maximum-entropy sampling

Authors: Marcia Fampa, Jon Lee

The maximum-entropy sampling problem (MESP) seeks, for an order-$n$ covariance matrix $C$, a principal submatrix of order $s$ with maximum log-determinant. Mostly for convenience, we assume that $C$ is nonsingular. Al-Thani and Lee (2023) solved MESP in $O(n^5)$ time when $C$ or $C^{-1}$ is tridiagonal. We show that the inner maximization of their recursion depends only on a prefix of the index set and that no piece of a solution is longer than $s$; this gives an $O(ns^2)$-time algorithm that returns the optimal value for every budget $t\le s$. When $C^{-1}$ is tridiagonal, $C$ is, up to scaling, the covariance matrix of an Ornstein--Uhlenbeck process observed at unevenly spaced times, and MESP becomes choosing points on a line under a concave gap function with the Monge property; this gives an $O(ns)$-time algorithm and, in the first-order autoregressive case, a closed-form solution. Given only $C$, we solve MESP in $O(n^2)$ time whenever $C$ or $C^{-1}$ is tridiagonal, up to a symmetric permutation, and we recognize these cases within the same bound. For spiders, we make explicit, and sharpen, the dependence on the number of legs, and, drawing on a hardness result of Ohsaka for stars, we observe that, unless $\mathrm{P}=\mathrm{NP}$, the exponent of the running time must grow with the number of legs.

Authors: Marcia Fampa, Jon Lee

The maximum-entropy sampling problem (MESP) seeks, for an order-$n$ covariance matrix $C$, a principal submatrix of order $s$ with maximum log-determinant. Mostly for convenience, we assume that $C$ is nonsingular. Al-Thani and Lee (2023) solved MESP in $O(n^5)$ time when $C$ or $C^{-1}$ is tridiagonal. We show that the inner maximization of their recursion depends only on a prefix of the index set and that no piece of a solution is longer than $s$; this gives an $O(ns^2)$-time algorithm that returns the optimal value for every budget $t\le s$. When $C^{-1}$ is tridiagonal, $C$ is, up to scaling, the covariance matrix of an Ornstein--Uhlenbeck process observed at unevenly spaced times, and MESP becomes choosing points on a line under a concave gap function with the Monge property; this gives an $O(ns)$-time algorithm and, in the first-order autoregressive case, a closed-form solution. Given only $C$, we solve MESP in $O(n^2)$ time whenever $C$ or $C^{-1}$ is tridiagonal, up to a symmetric permutation, and we recognize these cases within the same bound. For spiders, we make explicit, and sharpen, the dependence on the number of legs, and, drawing on a hardness result of Ohsaka for stars, we observe that, unless $\mathrm{P}=\mathrm{NP}$, the exponent of the running time must grow with the number of legs.

Wednesday, October 07 2026, 00:00

Almost Tight Bounds for Isomorphism Testing and Basis Construction in Finite Abelian Groups

Authors: Nader H. Bshouty

We study isomorphism decision and basis construction for finite Abelian groups of known order $n$. We measure complexity by the number of additions performed in the groups and by the total running time. We give a randomized isomorphism decision algorithm that performs $\tilde O(n^{1/4})$ group additions and runs in $\tilde O(n^{1/4})$ time. This improves the $\tilde O(\sqrt n)$ upper bound of Chen and Fu and matches Bshouty $Ω(n^{1/4})$ lower bound up to polylogarithmic factors. We also prove that finding a basis with success probability at least $2/3$ requires $Ω(\sqrt n)$ group additions in the worst case. This matches the $\tilde O(\sqrt n)$ upper bound of Chen and Fu up to polylogarithmic factors. These results separate isomorphism decision from basis construction in finite Abelian groups: their optimal worst-case complexities are $\tildeΘ(n^{1/4})$ and $\tildeΘ(\sqrt n)$, respectivel

Authors: Nader H. Bshouty

We study isomorphism decision and basis construction for finite Abelian groups of known order $n$. We measure complexity by the number of additions performed in the groups and by the total running time. We give a randomized isomorphism decision algorithm that performs $\tilde O(n^{1/4})$ group additions and runs in $\tilde O(n^{1/4})$ time. This improves the $\tilde O(\sqrt n)$ upper bound of Chen and Fu and matches Bshouty $Ω(n^{1/4})$ lower bound up to polylogarithmic factors. We also prove that finding a basis with success probability at least $2/3$ requires $Ω(\sqrt n)$ group additions in the worst case. This matches the $\tilde O(\sqrt n)$ upper bound of Chen and Fu up to polylogarithmic factors. These results separate isomorphism decision from basis construction in finite Abelian groups: their optimal worst-case complexities are $\tildeΘ(n^{1/4})$ and $\tildeΘ(\sqrt n)$, respectivel

Wednesday, October 07 2026, 00:00

Efficient Posterior Sampling for $\mathbb Z_2$ Synchronization

Authors: Zhangsong Li

Consider the $\mathbb Z_2$ synchronization problem \[ \boldsymbol{Y} = \fracλ{\sqrt n} θθ^{\top} + \boldsymbol{Z}, \] where $θ$ is uniform on $\{-1,1\}^n$ and $\boldsymbol{Z}$ is an independent Gaussian Wigner matrix with off-diagonal variance one. We give a polynomial-time posterior sampling algorithm for every fixed $λ>1$, for which the conditional output law converges to the posterior in total variation, in expectation over the observation. The construction combines sequential TAP proposals with an independence Metropolis correction. The key is to control signed overlaps after logarithmic pinning and conditional TAP approximations along a random revealing path, which give an efficiently evaluable proposal with a polynomial density-ratio bound outside a set of vanishing posterior mass. To the best of our knowledge, this is the first polynomial-time posterior sampler for $\mathbb Z_2$ synchronization with a total-variation guarantee throughout the supercritical regime. For comparison, the diffusion-based sampler of \cite{montanari2023posterior} gives normalized Wasserstein guarantees at sufficiently large fixed signal-to-noise ratio.

Authors: Zhangsong Li

Consider the $\mathbb Z_2$ synchronization problem \[ \boldsymbol{Y} = \fracλ{\sqrt n} θθ^{\top} + \boldsymbol{Z}, \] where $θ$ is uniform on $\{-1,1\}^n$ and $\boldsymbol{Z}$ is an independent Gaussian Wigner matrix with off-diagonal variance one. We give a polynomial-time posterior sampling algorithm for every fixed $λ>1$, for which the conditional output law converges to the posterior in total variation, in expectation over the observation. The construction combines sequential TAP proposals with an independence Metropolis correction. The key is to control signed overlaps after logarithmic pinning and conditional TAP approximations along a random revealing path, which give an efficiently evaluable proposal with a polynomial density-ratio bound outside a set of vanishing posterior mass. To the best of our knowledge, this is the first polynomial-time posterior sampler for $\mathbb Z_2$ synchronization with a total-variation guarantee throughout the supercritical regime. For comparison, the diffusion-based sampler of \cite{montanari2023posterior} gives normalized Wasserstein guarantees at sufficiently large fixed signal-to-noise ratio.

Wednesday, October 07 2026, 00:00

3SUM is false

from Emanuele Viola

I was just pointed to arxiv.org/abs/2610.06783v1 wow! Another item for my growing list of disproved conjectures in my book… told ya that P=NP!

I was just pointed to https://arxiv.org/abs/2610.06783v1 wow! Another item for my growing list of disproved conjectures in my book… told ya that P=NP!

By Manu

Tuesday, October 06 2026, 15:33

TR26-232 | Reed-Solomon Codes at Capacity: Algorithmic List-Decoding and Proximity Gaps | Prahladh Harsha, Mrinal Kumar, Ramprasad Saptharishi

from ECCC Papers

Understanding the limits of list-decodability of Reed-Solomon codes has been one of the most important open problems in algebraic coding theory. Recently, Brakensiek, Chen, Putterman, Zhang, and Zheng, in a remarkable breakthrough, showed that Reed-Solomon (RS) codes over fields of large characteristic are algorithmically list-decodable all the way up to capacity. Building on this result, Jeronimo subsequently extended these techniques to solve the proximity-gaps question for RS codes. In this article, we give a unified and transparent exposition of these results.

Tuesday, October 06 2026, 15:00

Too Big to Fail

from Ben Recht

The obsession with and futility of macroeconomic forecasting

Hi there, argmin readers! Today’s post is a live blog of Class 10 of my graduate seminar “Forecasting: A Critical Retrospective.” The syllabus and list of past posts are here.

All of my cybernetically inclined friends are into Friedrich Hayek, but my research and teaching keep bringing me back to John Maynard Keynes. These two gentlemen occupy the two poles of the dialectic of the American Experiment. Hayek famously introduced the notion of markets as distributed computers, where prices carry knowledge across the economy. Keynes, with his economic theory of central banking, set the stage for centralized computing of economic variables to govern those markets.

In Keynes’ paradigm-shifting 1936 work, The General Theory of Employment, Interest, and Money, he lays out an oxymoronic formula for central planning in capitalist societies.1 The basics of the Keynesian model are laid out in the appendix of Robert Evans’ paper from this week’s reading. The national economy has four key variables: the amount of investment firms make into the economy, the amount of savings firms accumulate in financial instruments or by paying down debt, the demand for money in the economy to facilitate purchases and sales, and the supply of money from the government. To change these variables, the government can enact various policies. For example, it can invest in infrastructure, raise taxes, increase the money supply, or change interest rates. Keynes argues that the government can dictate the economy’s output—and hence the general welfare of all citizens, who are players in the big macroeconomic game—by properly executing its policy apparatus.

This would set the stage for the subsequent 90 years of democratic capitalist monetary policy. The government has to make policy to ensure a well-run economy. To do this, it has to know the current state of national investment and savings. It also has to be able to forecast what these variables will be if no policy changes are enacted. This last requirement has driven the major investment in macroeconomic forecasting.

Forecasting in macroeconomics is thus primarily a tool of control. Here I mean control in the academic sense: the theory of dynamical systems with inputs and outputs and the design of subsystems to drive outputs to desired targets. Keynes casts the economy as a giant control problem, where the goal is to deftly change policy to ensure a particular state of economic output and employment. It should be no surprise that tools from control, notably the work of Rudolf Kalman on optimal filtering and control of linear systems with quadratic objectives, play a central role in macroeconomics.

Now, to filter and control, we need to make predictions. Keynes didn’t tell us how to generate those predictions. But his disciples, in what is often called “Keynesian” macroeconomic forecasting, write down structural equations of the economy, fit the parameters of these equations using varied means, and then make forecasts directly from the fitted models.

This program of prediction ran into several obstacles. First, it requires mathematical equations that predict all of the aspects of the economy needed to precisely determine optimal policies. Second, it requires a massive measurement system to pin down all the relevant factors in the model. Both were terribly daunting and required a great deal of expert judgment.

Economists want their methods to be “scientific,” since they influence decisions with major consequences. However, with so many variables, so little stationarity in economic conditions, and so much politics involved, building a truly objective and replicable system seems like a fool’s errand. Beatrice Cherrier details some of the typically arbitrary, political nature of macroeconomic sausage-making in this blog post. Evans details the amount of analytical flexibility and expert judgment forecasters necessarily employ in their predictive techniques.

Beyond these nuances of modeling and measurement, however, a fundamental problem of feedback control remains insurmountable. The models have a ton of parameters that are fit to historical data. Different policies yield different parameters. These parameters change when a policy changes. And you can’t predict what the parameters will be after a policy changes. So what on earth are we doing?

The critique in the previous paragraph was levied at macroeconomic forecasting by Robert Lucas in 1976. That macroeconomic forecasting is still an influential practice 50 years later certainly tells us something. Macroeconomic forecasters occupied positions of power and held a sense of civic duty. So they took Lucas’ critique as a challenge, not a reason to close up shop.

I’m not going to hash out the various attempts to build complex, nonparametric macroeconomic models that add ornate complexity while failing to dodge the fundamental problem. Theoretical critiques can carry only so much weight. The fact that the Great Recession was substantially caused by terrible financial policy and inadequate forecasting should have been the nail in the coffin. In 2003, Robert Lucas himself declared that macroeconomics had been a great success:

“My thesis in this lecture is that macroeconomics in this original sense has succeeded: Its central problem of depression prevention has been solved, for all practical purposes, and has in fact been solved for many decades.”

Oops.

Economists didn’t see a problem with the deep instability created by hyperfinancialization. Indeed, though Evans did his ethnographic research on macroeconomists a decade before the crash, his point rings true:

“...[E]conomic policy cannot be based on a quantitative calculus of costs and benefits and must, instead, rest on the considered judgement of a community of experts. Macroeconomic modellers may be those experts, but to expect anything more from them is to expect too much.”

So who should we trust? The Obama administration hoped economists could help get us out of the mess. But 8 years of attempted neoliberal patching of the American system ended in such broad dissatisfaction that… well, you know what happened. We’ve since had a decade of federal unrest as we try to unmoor ourselves from the expertise of economists. While I don’t believe the Biden and Trump administrations have found themselves a suitable alternative, I make no predictions about whose policy advice we’ll be deferring ot next.

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1

The quote from last week’s post was from a rebuttal Keynes wrote to critics of this book.

By Ben Recht

Tuesday, October 06 2026, 14:32

Designated Sets in Concurrent Simplex and Alpenglow

from Decentralized Thoughts

Recent consensus protocols like Alpenglow or Concurrent Simplex run two confirmation paths concurrently: a “slow” path with two voting rounds, each using a small quorum, and a “fast” path with a single voting round using a large quorum. The “slow” path can actually finish first because distances are not uniform in a geographically distributed system. Some parties are nearby, often on the same continent, while others are across an ocean....

By Ittai Abraham, Clément Burgelin, Antoine Murat, Joachim Neu

Recent consensus protocols like Alpenglow or Concurrent Simplex run two confirmation paths concurrently: a “slow” path with two voting rounds, each using a small quorum, and a “fast” path with a single voting round using a large quorum. The “slow” path can actually finish first because distances are not uniform in a geographically distributed system. Some parties are nearby, often on the same continent, while others are across an ocean....

By Ittai Abraham, Clément Burgelin, Antoine Murat, Joachim Neu

Tuesday, October 06 2026, 13:44

TR26-231 | Tarski Fixed Points in Quasi-FPT Queries | Xi Chen, Ruiquan Gao, Yuhao Li, Aviad Rubinstein, Mihalis Yannakakis

from ECCC Papers

We study the query complexity of finding a Tarski fixed point over $[n]^k$. Previous work has left a large gap between $\smash{{\Omega}(\log^2 n)}$ and $\smash{\log^{O(k)}n}$. We show that both of the previous upper and lower bounds were far from tight: for every $k\geq 3$, $$ \Omega\left((\log n)^{\frac{1}{2}\lceil \log k\rceil}\right)\le \textrm{Tarski}(n,k)\le O\left(5^k (\log n)^{\lceil \log k\rceil}\right).$$ Succinctly, up to the fixed-parameter factor of $5^k$, the complexity is settled at $(\log n)^{\Theta(\log k )}$. In particular, we obtain the first super-polynomial query lower bound for this problem.

Tuesday, October 06 2026, 02:39

Natural proofs for quantum state preparation lower bounds

Authors: Christine Li, Natalie Parham

We identify a barrier that helps explain why proving stronger quantum state-preparation lower bounds has been so difficult. In particular, we establish a quantum analogue of the Razborov-Rudich natural proofs barrier for state-preparation lower bounds. We call a property of quantum states \emph{natural} if it holds for a sufficiently large fraction of Haar-random states and can be efficiently tested when given all of the state's amplitudes. Under a standard cryptographic assumption, we show that no natural property can prove superpolynomial state-preparation lower bounds even against a fixed level of the Magic Hierarchy. We show that several existing state-preparation lower-bound techniques are natural in our sense, including arguments based on approximate degree, not being a unique ground state of a local Hamiltonian, and mutual information.

Authors: Christine Li, Natalie Parham

We identify a barrier that helps explain why proving stronger quantum state-preparation lower bounds has been so difficult. In particular, we establish a quantum analogue of the Razborov-Rudich natural proofs barrier for state-preparation lower bounds. We call a property of quantum states \emph{natural} if it holds for a sufficiently large fraction of Haar-random states and can be efficiently tested when given all of the state's amplitudes. Under a standard cryptographic assumption, we show that no natural property can prove superpolynomial state-preparation lower bounds even against a fixed level of the Magic Hierarchy. We show that several existing state-preparation lower-bound techniques are natural in our sense, including arguments based on approximate degree, not being a unique ground state of a local Hamiltonian, and mutual information.

Tuesday, October 06 2026, 00:00

Characterizing Quantum Advantage for Generalizations of the Boolean Hidden Matching Problem

Authors: Mark Bun, Joao F. Doriguello, John Kallaugher, Nadezhda Voronova

We study the one-way communication complexity of the $f$-Boolean Hidden Partition problem. Here, Alice is given an $n$-bit string and Bob is given $Ω(n)$ disjoint blocks of its indices together with a string of labels. Under the promise that the evaluations of $f$ on these blocks either agree with all of the labels or disagree with all of them, Bob must determine which is the case using a single message from Alice. This problem generalizes the Boolean Hidden Matching and Hidden Hypermatching problems, which capture the special case where $f$ is the parity function. We establish classical and quantum communication bounds for $f$-Boolean Hidden Partition in terms of the sign degree $d$ of $f$, proving a conjecture of Doriguello and Montanaro (TQC 2020). Their prior work gave logarithmic communication upper bounds for classical protocols when $d \le 1$ and quantum protocols when $d \le 2$, as well as polynomial lower bounds for certain structured functions with larger sign degree. We show that for every $f$ of sign degree $d \ge 2$, the randomized classical communication complexity of this problem is $Θ(n^{1-1/d})$ while its quantum communication complexity lies between $Ω(n^{1-2/d})$ and $\bO{n^{1-1/\lceil d/2 \rceil} \log n}$. This completely characterizes the functions $f$ admitting polynomial quantum advantage as those for which $d \ge 2$, with a new infinite family of exponential separations given by the case $d = 2$.

Authors: Mark Bun, Joao F. Doriguello, John Kallaugher, Nadezhda Voronova

We study the one-way communication complexity of the $f$-Boolean Hidden Partition problem. Here, Alice is given an $n$-bit string and Bob is given $Ω(n)$ disjoint blocks of its indices together with a string of labels. Under the promise that the evaluations of $f$ on these blocks either agree with all of the labels or disagree with all of them, Bob must determine which is the case using a single message from Alice. This problem generalizes the Boolean Hidden Matching and Hidden Hypermatching problems, which capture the special case where $f$ is the parity function. We establish classical and quantum communication bounds for $f$-Boolean Hidden Partition in terms of the sign degree $d$ of $f$, proving a conjecture of Doriguello and Montanaro (TQC 2020). Their prior work gave logarithmic communication upper bounds for classical protocols when $d \le 1$ and quantum protocols when $d \le 2$, as well as polynomial lower bounds for certain structured functions with larger sign degree. We show that for every $f$ of sign degree $d \ge 2$, the randomized classical communication complexity of this problem is $Θ(n^{1-1/d})$ while its quantum communication complexity lies between $Ω(n^{1-2/d})$ and $\bO{n^{1-1/\lceil d/2 \rceil} \log n}$. This completely characterizes the functions $f$ admitting polynomial quantum advantage as those for which $d \ge 2$, with a new infinite family of exponential separations given by the case $d = 2$.

Tuesday, October 06 2026, 00:00

Complexity separations for optimal matchgate-Clifford synthesis

Authors: Berta Casas, Diego García-Martín, Yuxuan Zhang

Clifford and matchgate circuits are canonical families of classically simulable quantum circuits. Their intersection, the matchgate-Clifford group, plays an important role in randomized fermionic protocols and in matchgate synthesis. Its adjoint action is isomorphic to the group of unit-determinant signed permutations of $2n$ Majorana modes, and we study optimal exact synthesis in this group. That is, given a target unitary and a gate set, output an $n$-qubit circuit implementing the target using the fewest operations. We show that the complexity of this problem strongly depends on the gate set. In particular, we study gate sets consisting of Majorana braids with different connectivity graphs. For path and complete graphs, we prove that the problem is classically solvable in $\mathcal{O}\left(n^2\right)$ time, and we provide explicit gate-optimal compilers. In addition, we prove that when the connectivity graph is a tree, the decision version of the optimal synthesis problem becomes NP-complete. Finally, we benchmark our optimal compiler on chains of up to $n=80$ qubits against those of \texttt{Qiskit} and \texttt{Tket}, obtaining circuits with constant factor improvements $\times2.57$ and $\times2.28$ in the total number of gates, respectively.

Authors: Berta Casas, Diego García-Martín, Yuxuan Zhang

Clifford and matchgate circuits are canonical families of classically simulable quantum circuits. Their intersection, the matchgate-Clifford group, plays an important role in randomized fermionic protocols and in matchgate synthesis. Its adjoint action is isomorphic to the group of unit-determinant signed permutations of $2n$ Majorana modes, and we study optimal exact synthesis in this group. That is, given a target unitary and a gate set, output an $n$-qubit circuit implementing the target using the fewest operations. We show that the complexity of this problem strongly depends on the gate set. In particular, we study gate sets consisting of Majorana braids with different connectivity graphs. For path and complete graphs, we prove that the problem is classically solvable in $\mathcal{O}\left(n^2\right)$ time, and we provide explicit gate-optimal compilers. In addition, we prove that when the connectivity graph is a tree, the decision version of the optimal synthesis problem becomes NP-complete. Finally, we benchmark our optimal compiler on chains of up to $n=80$ qubits against those of \texttt{Qiskit} and \texttt{Tket}, obtaining circuits with constant factor improvements $\times2.57$ and $\times2.28$ in the total number of gates, respectively.

Tuesday, October 06 2026, 00:00

Recognizers for Graph-Encoding Languages

Authors: Anssi Yli-Jyrä

We introduce recurrent incidence automata (RIAs), a new automaton model motivated by a decomposition of certain two-stack visibly pushdown computations. The decomposition separates vertex-local finite-state computations from recurrent one-stack interfaces connecting consecutive vertices. The construction is motivated by a two-stack visibly pushdown encoding of arbitrary ordered graphs whose strings admit a unique factorization into center-foldable vertex-local factors and whose auxiliary stack is empty at every factor boundary. Folding each factor into a sequence of pair symbols yields a local interface transformation. An RIA consists of a finite-state unit that computes these transformations and a recurrent layer that composes them across consecutive factors. Rather than manipulating an internal pushdown store, RIAs externalize long-range stack memory into recurrent interfaces between local computations. We show that nondeterministic RIA languages are closed under union, intersection, concatenation, Kleene-*, and reversal. Deterministic RIAs are closed under Boolean operations, although emptiness remains undecidable.

Authors: Anssi Yli-Jyrä

We introduce recurrent incidence automata (RIAs), a new automaton model motivated by a decomposition of certain two-stack visibly pushdown computations. The decomposition separates vertex-local finite-state computations from recurrent one-stack interfaces connecting consecutive vertices. The construction is motivated by a two-stack visibly pushdown encoding of arbitrary ordered graphs whose strings admit a unique factorization into center-foldable vertex-local factors and whose auxiliary stack is empty at every factor boundary. Folding each factor into a sequence of pair symbols yields a local interface transformation. An RIA consists of a finite-state unit that computes these transformations and a recurrent layer that composes them across consecutive factors. Rather than manipulating an internal pushdown store, RIAs externalize long-range stack memory into recurrent interfaces between local computations. We show that nondeterministic RIA languages are closed under union, intersection, concatenation, Kleene-*, and reversal. Deterministic RIAs are closed under Boolean operations, although emptiness remains undecidable.

Tuesday, October 06 2026, 00:00

Separating ClonableQMA and QCMA Relative to a Classical Oracle

Authors: Alper Cakan, Kai-Min Chung, Wei-Hsiang Hung, Tzu-Yi Yang

Since the introduction of the complexity class QMA as a quantum-verifier analogue of NP (Kitaev, 1997), many have wondered whether quantum proofs are necessary or classical proofs suffice - that is, whether QMA = QCMA or QCMA != QMA (Aharonov and Naveh, 2002; Aaronson and Kuperberg, CCC '07). This longstanding question was recently answered by works of Bostanci, Haferkamp, Nirkhe, and Zhandry (STOC '26) and Bostanci, Huang, and Vaikuntanathan (FOCS '26), which showed that quantum proofs are more powerful than classical ones in the classical-oracle setting. However, it remains unclear what exactly makes quantum proofs more powerful than classical ones. In the information-theoretic setting, a family of quantum states is not classicalizable if and only if it is unclonable. Indeed, these recent works also explicitly highlight the unclonability of their quantum proofs as a key mechanism behind their separations, and their arguments crucially rely on this property. This raises the question of whether unclonability is necessary for quantum proofs to be more powerful than classical ones. In this work, we show that even clonable quantum proofs can be more powerful than classical ones relative to a classical oracle by constructing a classical oracle O such that QCMA^O != ClonableQMA^O. This resolves the open question of Nehoran and Zhandry (ITCS '24), who established the analogous separation relative to a quantum oracle. We also show a classical-oracle separation between BQP/clonableqpoly and BQP/poly, and give applications of our results to quantum cryptography.

Authors: Alper Cakan, Kai-Min Chung, Wei-Hsiang Hung, Tzu-Yi Yang

Since the introduction of the complexity class QMA as a quantum-verifier analogue of NP (Kitaev, 1997), many have wondered whether quantum proofs are necessary or classical proofs suffice - that is, whether QMA = QCMA or QCMA != QMA (Aharonov and Naveh, 2002; Aaronson and Kuperberg, CCC '07). This longstanding question was recently answered by works of Bostanci, Haferkamp, Nirkhe, and Zhandry (STOC '26) and Bostanci, Huang, and Vaikuntanathan (FOCS '26), which showed that quantum proofs are more powerful than classical ones in the classical-oracle setting. However, it remains unclear what exactly makes quantum proofs more powerful than classical ones. In the information-theoretic setting, a family of quantum states is not classicalizable if and only if it is unclonable. Indeed, these recent works also explicitly highlight the unclonability of their quantum proofs as a key mechanism behind their separations, and their arguments crucially rely on this property. This raises the question of whether unclonability is necessary for quantum proofs to be more powerful than classical ones. In this work, we show that even clonable quantum proofs can be more powerful than classical ones relative to a classical oracle by constructing a classical oracle O such that QCMA^O != ClonableQMA^O. This resolves the open question of Nehoran and Zhandry (ITCS '24), who established the analogous separation relative to a quantum oracle. We also show a classical-oracle separation between BQP/clonableqpoly and BQP/poly, and give applications of our results to quantum cryptography.

Tuesday, October 06 2026, 00:00

Subsequence Analysis Problems for Binary Parikh Matrices

Authors: Szilárd Zsolt Fazekas, Xinhao Huang, Robert Mercaş

The universality index corresponding to a word is the largest integer k such that every word of length k over the given alphabet occurs in it as a subsequence. Relative to languages this notion can be investigated with respect to both existential and universal quantifiers, with the former corresponding to the existence of a word in the language with universality index at least k, while the latter considers the index across all words that the language contains. In this work we study the existential (exists-universality) and universal (forall-universality) subsequence universality (as introduced in [Adamson et al., ISAAC 2023]) for binary languages consisting of all words with a fixed number of letters a, letters b, and subsequences ab. We prove that both exists- and forall-universality admit exact arithmetic characterizations for these languages. Extending the above notions, we end the paper by initiating the analysis of the probability of a fixed word occurring as subsequence of the words in such a language. To this end, we prove that, for every fixed pattern word w and an error tolerance, given as input the subsequence counts describing a language, the ratio of words in the language having the pattern w as a subsequence admits an additive approximation scheme that is polynomial-time in the binary encoding of the input counts.

Authors: Szilárd Zsolt Fazekas, Xinhao Huang, Robert Mercaş

The universality index corresponding to a word is the largest integer k such that every word of length k over the given alphabet occurs in it as a subsequence. Relative to languages this notion can be investigated with respect to both existential and universal quantifiers, with the former corresponding to the existence of a word in the language with universality index at least k, while the latter considers the index across all words that the language contains. In this work we study the existential (exists-universality) and universal (forall-universality) subsequence universality (as introduced in [Adamson et al., ISAAC 2023]) for binary languages consisting of all words with a fixed number of letters a, letters b, and subsequences ab. We prove that both exists- and forall-universality admit exact arithmetic characterizations for these languages. Extending the above notions, we end the paper by initiating the analysis of the probability of a fixed word occurring as subsequence of the words in such a language. To this end, we prove that, for every fixed pattern word w and an error tolerance, given as input the subsequence counts describing a language, the ratio of words in the language having the pattern w as a subsequence admits an additive approximation scheme that is polynomial-time in the binary encoding of the input counts.

Tuesday, October 06 2026, 00:00

Random-Oracle Unitary Synthesis is Impossible

Authors: Andrew Huang, Akshar Ramkumar, John Wright

A major open problem in quantum complexity is the question of unitary synthesis---namely, is it possible to efficiently implement any unitary, given the ability to evaluate any classical function in superposition? Inspired by a recent work by Brakerski and Yuen (CRYPTO 2026), we propose an ``average-case'' unitary synthesis problem, which asks whether it is possible to efficiently implement a Haar random unitary given access to a random Boolean function. We then demonstrate a superpolynomial query lower bound, establishing that unitary synthesis in this model is impossible. Along with our main result, we settle in the negative a question Brakerski and Yuen pose, of whether scalable pseudorandom unitaries (PRUs) can be implemented in the ROM-PRU model. In particular, we show that in the ROM-PRU model, no $Ω(N^{1+γ})$ unitary design on $n$ qubits, where $N=2^n$, can be efficiently achieved for any $γ> 0$. On the other hand, we construct an $O(N)$-design in $\text{poly}(n)$ queries in the same model, surpassing the previously best known results which constructed $O(\sqrt{N})$-designs.

Authors: Andrew Huang, Akshar Ramkumar, John Wright

A major open problem in quantum complexity is the question of unitary synthesis---namely, is it possible to efficiently implement any unitary, given the ability to evaluate any classical function in superposition? Inspired by a recent work by Brakerski and Yuen (CRYPTO 2026), we propose an ``average-case'' unitary synthesis problem, which asks whether it is possible to efficiently implement a Haar random unitary given access to a random Boolean function. We then demonstrate a superpolynomial query lower bound, establishing that unitary synthesis in this model is impossible. Along with our main result, we settle in the negative a question Brakerski and Yuen pose, of whether scalable pseudorandom unitaries (PRUs) can be implemented in the ROM-PRU model. In particular, we show that in the ROM-PRU model, no $Ω(N^{1+γ})$ unitary design on $n$ qubits, where $N=2^n$, can be efficiently achieved for any $γ> 0$. On the other hand, we construct an $O(N)$-design in $\text{poly}(n)$ queries in the same model, surpassing the previously best known results which constructed $O(\sqrt{N})$-designs.

Tuesday, October 06 2026, 00:00

Explicit Nonlinear Functions beyond the Fourier bound

Authors: Swastik Kopparty, Rishabh Kothary, Shanthanu S. Rai

We study the problem of constructing highly nonlinear vectorial maps $F: \mathbb F_2^n \to \mathbb F_2^m$. Concretely, we want an $F$ and an $A = A(m,n)> 0$ as small as possible, so that for every affine map $L: \mathbb F_2^n \to \mathbb F_2^m$ (of the form $L(x) = M x + b $) we have: $$\mathrm{agree}(F, L) := |\{ x \in \mathbb F_2^n \mid F(x) = L(x) \}| \leq A.$$ Such questions have been studied by Nyberg (1991,1993), Carlet and Ding (2004,2007), Liu, Mesnager and Chen (2017), Nagy (2025), and Biryukov, Turecek, and Udovenko (2026). There is a classical method of constructing such functions from bent-functions and Fourier analytic ideas; the best bound achievable by this method is: $$ A(m,n) = Θ(2^{n-m} + 2^{n/2}),$$ and in particular, is never smaller than $2^{n/2}$. In this work, we show how to construct highly nonlinear functions beyond this Fourier bound. Concretely, we show how to construct for every $γ>0$, a function $F: \mathbb F_2^n \to \mathbb F_2^m$ with $m = O_γ(n)$, achieving $$ A(m,n) \leq (1 + γ)^n.$$ Surprisingly, we even achieve the same quantitative behavior for the much harder question of having low agreement with $m$-tuples of degree $d$ polynomials $Q: \mathbb F_2^n \to \mathbb F_2^m$, with $m = O_{γ, d}(n)$. Here the previously best bounds were of the form $A(m,n) = O( 2^{-\frac{n}{2^{d+1}}} \cdot 2^n )$ of Ben-Sasson and Kopparty (2010), based on Gowers-norm-type arguments. All our results generalize to all finite fields $\mathbb F_q$ in place of $\mathbb F_2$. Our methods are based on a new connection to classical results on counting solutions to systems of polynomial equations via algebraic methods. This connection brings us to basic questions in combinatorics, about graphs and hypergraphs with simultaneously a small number of edges and independent sets.

Authors: Swastik Kopparty, Rishabh Kothary, Shanthanu S. Rai

We study the problem of constructing highly nonlinear vectorial maps $F: \mathbb F_2^n \to \mathbb F_2^m$. Concretely, we want an $F$ and an $A = A(m,n)> 0$ as small as possible, so that for every affine map $L: \mathbb F_2^n \to \mathbb F_2^m$ (of the form $L(x) = M x + b $) we have: $$\mathrm{agree}(F, L) := |\{ x \in \mathbb F_2^n \mid F(x) = L(x) \}| \leq A.$$ Such questions have been studied by Nyberg (1991,1993), Carlet and Ding (2004,2007), Liu, Mesnager and Chen (2017), Nagy (2025), and Biryukov, Turecek, and Udovenko (2026). There is a classical method of constructing such functions from bent-functions and Fourier analytic ideas; the best bound achievable by this method is: $$ A(m,n) = Θ(2^{n-m} + 2^{n/2}),$$ and in particular, is never smaller than $2^{n/2}$. In this work, we show how to construct highly nonlinear functions beyond this Fourier bound. Concretely, we show how to construct for every $γ>0$, a function $F: \mathbb F_2^n \to \mathbb F_2^m$ with $m = O_γ(n)$, achieving $$ A(m,n) \leq (1 + γ)^n.$$ Surprisingly, we even achieve the same quantitative behavior for the much harder question of having low agreement with $m$-tuples of degree $d$ polynomials $Q: \mathbb F_2^n \to \mathbb F_2^m$, with $m = O_{γ, d}(n)$. Here the previously best bounds were of the form $A(m,n) = O( 2^{-\frac{n}{2^{d+1}}} \cdot 2^n )$ of Ben-Sasson and Kopparty (2010), based on Gowers-norm-type arguments. All our results generalize to all finite fields $\mathbb F_q$ in place of $\mathbb F_2$. Our methods are based on a new connection to classical results on counting solutions to systems of polynomial equations via algebraic methods. This connection brings us to basic questions in combinatorics, about graphs and hypergraphs with simultaneously a small number of edges and independent sets.

Tuesday, October 06 2026, 00:00

Unitary RQL Equals RQL

Authors: Quinten Tupker

Intermediate measurements let quantum computations discard information and reuse their workspace. Deferring all measurements can require storing their entire history, which need not preserve logarithmic space. Fefferman and Remscrim proved that measurements can nevertheless be eliminated with two-sided bounded error, and asked whether the same holds with one-sided error [FR21]. We prove RQLΓ = RQULΓ for the standard gate set Γ = {H, T, CNOT}, preserving polynomial time, logarithmic space, and exactly zero acceptance on no-instances. Our proof extends the density-matrix doubling method of Girish, Raz and Zhan [ GRZ21 ] to general channels, including resets and classical memory. We also prove measurement elimination for broader finite gate sets with exact inverses, including suitable gates with transcendental entries, and establish gate-set independence for a specified family of algebraic gate sets. A separate history-checking construction proves QMAL1,G = QUMAL1,G under explicit gate assumptions: measurements can also be eliminated from logarithmic-space quantum verification while preserving perfect completeness

Authors: Quinten Tupker

Intermediate measurements let quantum computations discard information and reuse their workspace. Deferring all measurements can require storing their entire history, which need not preserve logarithmic space. Fefferman and Remscrim proved that measurements can nevertheless be eliminated with two-sided bounded error, and asked whether the same holds with one-sided error [FR21]. We prove RQLΓ = RQULΓ for the standard gate set Γ = {H, T, CNOT}, preserving polynomial time, logarithmic space, and exactly zero acceptance on no-instances. Our proof extends the density-matrix doubling method of Girish, Raz and Zhan [ GRZ21 ] to general channels, including resets and classical memory. We also prove measurement elimination for broader finite gate sets with exact inverses, including suitable gates with transcendental entries, and establish gate-set independence for a specified family of algebraic gate sets. A separate history-checking construction proves QMAL1,G = QUMAL1,G under explicit gate assumptions: measurements can also be eliminated from logarithmic-space quantum verification while preserving perfect completeness

Tuesday, October 06 2026, 00:00

Fractal Gadgets for Neural Networks: The Complexity of the Narrow Regime

Authors: Olivier Bournez, Johanne Cohen, Laura Cohen, Adrian Wurm

We study the verification problem for deep narrow ReLU neural networks: given a network of bounded width computing a piecewise-affine map on [0,1], does some input satisfy a prescribed output constraint? Classical NP-hardness proofs for ReLU verification use one neuron per Boolean variable and say nothing about networks of small constant width, while width-1 networks are easy to verify. We show that verification of ReLU networks is NP-complete at width 4 for arbitrary inputs in [0,1]. When inputs are restricted to a natural discrete encoding set, NP-completeness already holds at width 3. Together with polynomial-time decidability at width 1, this leaves open only width 2 on the encoding set, and widths 2 and 3 on [0,1]. The technical core is a fractal preprocessing gadget: a width-2 ReLU subnetwork whose iterate vanishes precisely near a finite Cantor-like subset of [0,1] with 2^n points. It reduces verification of a continuous function on [0,1] to verification on 2^n discrete points without increasing the width, and is the missing ingredient for width-bounded hardness reductions. The same construction yields further results at width 3 on the encoding set: the universal problem is coNP-complete, counting zeros is #P-complete, a majority variant is PP-complete, and approximating the minimum output within a constant gap inherited from Max-3Sat is NP-hard. The NP, coNP and inapproximability results lift to all of [0,1] at width 4; lifting counting and majority, and lifting at width 3, remain open.

Authors: Olivier Bournez, Johanne Cohen, Laura Cohen, Adrian Wurm

We study the verification problem for deep narrow ReLU neural networks: given a network of bounded width computing a piecewise-affine map on [0,1], does some input satisfy a prescribed output constraint? Classical NP-hardness proofs for ReLU verification use one neuron per Boolean variable and say nothing about networks of small constant width, while width-1 networks are easy to verify. We show that verification of ReLU networks is NP-complete at width 4 for arbitrary inputs in [0,1]. When inputs are restricted to a natural discrete encoding set, NP-completeness already holds at width 3. Together with polynomial-time decidability at width 1, this leaves open only width 2 on the encoding set, and widths 2 and 3 on [0,1]. The technical core is a fractal preprocessing gadget: a width-2 ReLU subnetwork whose iterate vanishes precisely near a finite Cantor-like subset of [0,1] with 2^n points. It reduces verification of a continuous function on [0,1] to verification on 2^n discrete points without increasing the width, and is the missing ingredient for width-bounded hardness reductions. The same construction yields further results at width 3 on the encoding set: the universal problem is coNP-complete, counting zeros is #P-complete, a majority variant is PP-complete, and approximating the minimum output within a constant gap inherited from Max-3Sat is NP-hard. The NP, coNP and inapproximability results lift to all of [0,1] at width 4; lifting counting and majority, and lifting at width 3, remain open.

Tuesday, October 06 2026, 00:00

The Complexity of Computing Nash Equilibria in Colonel Blotto Games

Authors: Vasilis Pollatos, Andreas Kontogiannis

We study the complexity of Nash equilibrium computation in discrete Colonel Blotto games. For two-player general-sum Colonel Blotto with monotonic piecewise-constant battlefield payoffs, we show that computing an inverse-polynomial approximate Nash equilibrium is PPAD-hard, even with only two battlefields and a constant number of pieces per battlefield, thereby resolving an open question of [KPF+25]. Allowing more battlefields, the hardness persists when every battlefield payoff is $2$-piecewise constant with respect to either player's allocation. A general PPAD-membership theorem for multiplayer Blotto with arbitrary local reward functions then implies PPAD-completeness for both hardness results. Motivated by fixed-rank bimatrix games, we then identify a tractable frontier within two-player general-sum Colonel Blotto. If the social payoff has rank-$r$ structure, then, for every fixed $r$, an $\varepsilon$-Nash equilibrium can be computed in time polynomial in $B_1,B_2,k$, and $1/\varepsilon$. Thus constant-rank two-player Colonel Blotto remains tractable despite its exponentially large pure strategy spaces. Finally, we study multiplayer winner-takes-all Colonel Blotto with player-specific battlefield values and uncover a sharp tie-breaking frontier. If every highest bidder receives her full battlefield value, an exact pure Nash equilibrium can be computed in polynomial time for arbitrary binary-encoded budgets. In contrast, under ordinary equal splitting among highest bidders, we prove that computing an inverse-polynomial-accuracy Nash equilibrium is PPAD-hard even with only five players. This resolves an open question posed in concurrent work by Bichler and Ghosh [BG26], who established PPAD-hardness in the same player-specific equal-splitting setting when the number of players grows with the instance and asked whether hardness persists for a constant number of players.

Authors: Vasilis Pollatos, Andreas Kontogiannis

We study the complexity of Nash equilibrium computation in discrete Colonel Blotto games. For two-player general-sum Colonel Blotto with monotonic piecewise-constant battlefield payoffs, we show that computing an inverse-polynomial approximate Nash equilibrium is PPAD-hard, even with only two battlefields and a constant number of pieces per battlefield, thereby resolving an open question of [KPF+25]. Allowing more battlefields, the hardness persists when every battlefield payoff is $2$-piecewise constant with respect to either player's allocation. A general PPAD-membership theorem for multiplayer Blotto with arbitrary local reward functions then implies PPAD-completeness for both hardness results. Motivated by fixed-rank bimatrix games, we then identify a tractable frontier within two-player general-sum Colonel Blotto. If the social payoff has rank-$r$ structure, then, for every fixed $r$, an $\varepsilon$-Nash equilibrium can be computed in time polynomial in $B_1,B_2,k$, and $1/\varepsilon$. Thus constant-rank two-player Colonel Blotto remains tractable despite its exponentially large pure strategy spaces. Finally, we study multiplayer winner-takes-all Colonel Blotto with player-specific battlefield values and uncover a sharp tie-breaking frontier. If every highest bidder receives her full battlefield value, an exact pure Nash equilibrium can be computed in polynomial time for arbitrary binary-encoded budgets. In contrast, under ordinary equal splitting among highest bidders, we prove that computing an inverse-polynomial-accuracy Nash equilibrium is PPAD-hard even with only five players. This resolves an open question posed in concurrent work by Bichler and Ghosh [BG26], who established PPAD-hardness in the same player-specific equal-splitting setting when the number of players grows with the instance and asked whether hardness persists for a constant number of players.

Tuesday, October 06 2026, 00:00

Dimension Amplification for Tarski Fixed-Point Query Lower Bounds

Authors: Boyu Liu, Zihe Wang

We prove that finding a fixed point of a monotone map on the nine-dimensional grid $[N]^9$ requires $Ω((\log N)^3)$ deterministic queries, even when the fixed point is unique and each query returns the entire function value. The proof gives a construction that raises the dimension from $d$ to $4d+1$, preserves uniqueness, and adds a logarithmic factor to the lower bound. Iteration gives $Ω((\log N)^{r+2})$ queries in dimension $(7\cdot4^r-1)/3$, for every fixed nonnegative integer $r$, with an implicit constant that may depend on $r$. Consequently, no finite logarithmic exponent bounds the query complexity in all fixed dimensions.

Authors: Boyu Liu, Zihe Wang

We prove that finding a fixed point of a monotone map on the nine-dimensional grid $[N]^9$ requires $Ω((\log N)^3)$ deterministic queries, even when the fixed point is unique and each query returns the entire function value. The proof gives a construction that raises the dimension from $d$ to $4d+1$, preserves uniqueness, and adds a logarithmic factor to the lower bound. Iteration gives $Ω((\log N)^{r+2})$ queries in dimension $(7\cdot4^r-1)/3$, for every fixed nonnegative integer $r$, with an implicit constant that may depend on $r$. Consequently, no finite logarithmic exponent bounds the query complexity in all fixed dimensions.

Tuesday, October 06 2026, 00:00

Optimal and Verifiable Quantum Advantages in Communication Complexity

Authors: Ryan Anselm, Michelle Ding, Dar Gilboa, Sabee Grewal

We establish optimal quantum-classical separations in communication complexity for search problems. We introduce a total search problem called Pelagic Fourier Fishing and show that it admits an $n$-qubit quantum one-way protocol, whereas every randomized two-way protocol requires $Ω(2^n)$ bits of communication. We then introduce a variant of this problem whose solutions can be verified in polynomial time. This variant also admits an $n$-qubit quantum one-way protocol, while every randomized one-way protocol requires $Ω(2^n)$ bits of communication. We also construct a family of efficiently verifiable total search problems achieving an $n$ versus $Ω_d(n^d)$ separation between quantum one-way and randomized one-way communication for every fixed $d \ge 2$. In the quantum protocol, Alice prepares her message using a single unitary from the $d$th level of the Clifford hierarchy, and Bob performs a Clifford measurement. This separation is asymptotically optimal under this restriction on Alice's message. For $d = 2$, Alice's message is a stabilizer state and Bob's measurement is Clifford, so the protocol uses no magic, yet achieves an optimal quadratic quantum advantage. Finally, we discuss how these separations can be adapted to near-term quantum advantage experiments in which the demonstrated advantage is both unconditional and efficiently verifiable.

Authors: Ryan Anselm, Michelle Ding, Dar Gilboa, Sabee Grewal

We establish optimal quantum-classical separations in communication complexity for search problems. We introduce a total search problem called Pelagic Fourier Fishing and show that it admits an $n$-qubit quantum one-way protocol, whereas every randomized two-way protocol requires $Ω(2^n)$ bits of communication. We then introduce a variant of this problem whose solutions can be verified in polynomial time. This variant also admits an $n$-qubit quantum one-way protocol, while every randomized one-way protocol requires $Ω(2^n)$ bits of communication. We also construct a family of efficiently verifiable total search problems achieving an $n$ versus $Ω_d(n^d)$ separation between quantum one-way and randomized one-way communication for every fixed $d \ge 2$. In the quantum protocol, Alice prepares her message using a single unitary from the $d$th level of the Clifford hierarchy, and Bob performs a Clifford measurement. This separation is asymptotically optimal under this restriction on Alice's message. For $d = 2$, Alice's message is a stabilizer state and Bob's measurement is Clifford, so the protocol uses no magic, yet achieves an optimal quadratic quantum advantage. Finally, we discuss how these separations can be adapted to near-term quantum advantage experiments in which the demonstrated advantage is both unconditional and efficiently verifiable.

Tuesday, October 06 2026, 00:00

Strong Refutation for Random Quantum 3-SAT at Constant Density

Authors: Siu On Chan, Jeff Xu

We give a classical polynomial-time algorithm that strongly refutes random quantum $3$-SAT at sufficiently large constant constraint density, thereby disproving the quantum analogue of Feige's random $3$-SAT hypothesis. This stands in sharp contrast to classical random $3$-SAT, for which polynomial-time strong refutation is known only at constraint density $Δ\gtrsim n^{1/2}$. Although quantum $3$-SAT shares the pairwise-independence barrier of its classical counterpart, our SDP-based refutation overcomes this barrier by exploiting the noncommutativity of quantum constraints.

Authors: Siu On Chan, Jeff Xu

We give a classical polynomial-time algorithm that strongly refutes random quantum $3$-SAT at sufficiently large constant constraint density, thereby disproving the quantum analogue of Feige's random $3$-SAT hypothesis. This stands in sharp contrast to classical random $3$-SAT, for which polynomial-time strong refutation is known only at constraint density $Δ\gtrsim n^{1/2}$. Although quantum $3$-SAT shares the pairwise-independence barrier of its classical counterpart, our SDP-based refutation overcomes this barrier by exploiting the noncommutativity of quantum constraints.

Tuesday, October 06 2026, 00:00

A Dichotomy for Planar Graph Homomorphisms with Nonnegative Weights

Authors: Chenghua Liu, Boning Meng

We prove a complete complexity dichotomy for planar graph homomorphism counting with any fixed symmetric nonnegative matrix of arbitrary finite order, giving an explicit criterion for tractability. We also characterize exactly which fixed positive vertex weights preserve tractability, with both classifications extending from algebraic weights to fixed real weights in a prescribed exact representation. Our proof hinges on an entropy-based continuation argument: maximal logarithmic support identifies distance kernels as maximum-entropy completions, extending their positive definiteness throughout the parameter interval. This enables distance geometry to recover hidden product coordinates even when planar gadgets cannot distinguish colors; counting-hardness arguments then force the factors to be zero-field Boolean Ising interactions. The classification also yields complete tractability criteria for clock models, coupled Ising systems, and planar contractions of stoquastic imaginary-time kernels. All results have been formally verified in Lean 4.

Authors: Chenghua Liu, Boning Meng

We prove a complete complexity dichotomy for planar graph homomorphism counting with any fixed symmetric nonnegative matrix of arbitrary finite order, giving an explicit criterion for tractability. We also characterize exactly which fixed positive vertex weights preserve tractability, with both classifications extending from algebraic weights to fixed real weights in a prescribed exact representation. Our proof hinges on an entropy-based continuation argument: maximal logarithmic support identifies distance kernels as maximum-entropy completions, extending their positive definiteness throughout the parameter interval. This enables distance geometry to recover hidden product coordinates even when planar gadgets cannot distinguish colors; counting-hardness arguments then force the factors to be zero-field Boolean Ising interactions. The classification also yields complete tractability criteria for clock models, coupled Ising systems, and planar contractions of stoquastic imaginary-time kernels. All results have been formally verified in Lean 4.

Tuesday, October 06 2026, 00:00

On the Computational Complexity of Problems: Formalizing Sensitivity to Uncertainty and Parametric Complexity Classes

Authors: Yannis Tzitzikas

Is the classical question $P \stackrel{?}{=} NP$ the right one for understanding the complexity of real-world computation? Traditional worst-case analysis characterizes complexity solely as a function of input size $n$. Yet tasks whose cost is exponential in general often run in polynomial or even linear time once specific structural constraints or partial inputs are known. For instance, the Partition Problem is solvable in linear time, a constant-time core step following linear-time verification, when its inputs satisfy a simple structural property, although no polynomial-time algorithm is known for it in general; Integer Factorization, by contrast, resists structural knowledge: no checkable property of the input is known to improve on the sub-exponential number-field-sieve bound. Classical worst-case analysis cannot explain this difference, because it collapses a whole spectrum of difficulty into a single pessimistic bound. This paper formally develops a comprehensive parametric and uncertainty-aware framework for computational complexity. We introduce the notion of \emph{Sensitivity to Uncertainty} (SU) and formalize the cost variation $Δ_P(n, K)$ under a given input property $K$; we define the uncertainty-vanishing metric $Ψ(n, K)$ and prove a fundamental \emph{Uncertainty Reduction Theorem} bridging cost variation and input uncertainty; and we introduce the parametric classes $P_U[K]$ and $NP_U[K]$ as a more practical, instance-level foundation, focused on certifiable structure, rather than distributional typicality, that resolves the gap between theoretical complexity and real-world tractability. We further show how the same uncertainty analysis supports practice: it enables deterministic SLA via Design-by-Contract informs tool-use and reasoning splits in agentic AI, and provides an explanation of when quantum computers achieve exponential speedup.

Authors: Yannis Tzitzikas

Is the classical question $P \stackrel{?}{=} NP$ the right one for understanding the complexity of real-world computation? Traditional worst-case analysis characterizes complexity solely as a function of input size $n$. Yet tasks whose cost is exponential in general often run in polynomial or even linear time once specific structural constraints or partial inputs are known. For instance, the Partition Problem is solvable in linear time, a constant-time core step following linear-time verification, when its inputs satisfy a simple structural property, although no polynomial-time algorithm is known for it in general; Integer Factorization, by contrast, resists structural knowledge: no checkable property of the input is known to improve on the sub-exponential number-field-sieve bound. Classical worst-case analysis cannot explain this difference, because it collapses a whole spectrum of difficulty into a single pessimistic bound. This paper formally develops a comprehensive parametric and uncertainty-aware framework for computational complexity. We introduce the notion of \emph{Sensitivity to Uncertainty} (SU) and formalize the cost variation $Δ_P(n, K)$ under a given input property $K$; we define the uncertainty-vanishing metric $Ψ(n, K)$ and prove a fundamental \emph{Uncertainty Reduction Theorem} bridging cost variation and input uncertainty; and we introduce the parametric classes $P_U[K]$ and $NP_U[K]$ as a more practical, instance-level foundation, focused on certifiable structure, rather than distributional typicality, that resolves the gap between theoretical complexity and real-world tractability. We further show how the same uncertainty analysis supports practice: it enables deterministic SLA via Design-by-Contract informs tool-use and reasoning splits in agentic AI, and provides an explanation of when quantum computers achieve exponential speedup.

Tuesday, October 06 2026, 00:00

Separations with Immunity Relative to a Random Oracle in Computational Complexity

Authors: Gabriel Istrate

Rossman, Servedio, and Tan proved that the polynomial hierarchy is infinite relative to a random oracle. This paper strengthens this celebrated result by considering \emph{strong separations}, witnessed by immune languages. The main result of the paper shows that with respect to a random oracle the levels of the polynomial hierarchy separate with immunity. Specifically, with probability one over a random oracle $A$, for every $k\geq 1$ there is a language in $Σ_{k}^{P,A}$ that is immune to $Π_{k}^{P,A}$, and, symmetrically, a language in $Π_{k}^{P,A}$ that is immune to $Σ_{k}^{P,A}$. We thus extend classical results due to Bennett and Gill and Vereshchagin. We accomplish this by developing a "rare-or-wrong" approach to strong separations. We highlight the flexibility of the approach by strengthening other separations with respect to a random oracle from the complexity-theoretic literature.

Authors: Gabriel Istrate

Rossman, Servedio, and Tan proved that the polynomial hierarchy is infinite relative to a random oracle. This paper strengthens this celebrated result by considering \emph{strong separations}, witnessed by immune languages. The main result of the paper shows that with respect to a random oracle the levels of the polynomial hierarchy separate with immunity. Specifically, with probability one over a random oracle $A$, for every $k\geq 1$ there is a language in $Σ_{k}^{P,A}$ that is immune to $Π_{k}^{P,A}$, and, symmetrically, a language in $Π_{k}^{P,A}$ that is immune to $Σ_{k}^{P,A}$. We thus extend classical results due to Bennett and Gill and Vereshchagin. We accomplish this by developing a "rare-or-wrong" approach to strong separations. We highlight the flexibility of the approach by strengthening other separations with respect to a random oracle from the complexity-theoretic literature.

Tuesday, October 06 2026, 00:00

Training Variational Quantum Algorithms Is NP-Hard, Even Locally

Authors: Dax Enshan Koh, Triscia Mundo, Iosif Sakos, Antonios Varvitsiotis

Variational quantum algorithms (VQAs) generally rely on classical optimization to train parameterized quantum circuits. This training seeks to minimize an objective function, and its efficiency is central to the practical success of these algorithms. However, globally minimizing such training objectives over the circuit parameters is known to be $\mathsf{NP}$-hard, limiting the prospect of general guarantees for efficient training. In this Letter, we prove that even the weaker task of finding a local minimum of such VQA training objectives is strongly $\mathsf{NP}$-hard, including when the objective admits efficient classical evaluation. Moreover, we show that this hardness persists even for the task of finding a parameter vector within $\ell_p$-distance strictly less than $π/2$ of some local minimizer, for every $p\geq 1$. Our central technical result is that approximating a local minimizer of a Hermitian trigonometric polynomial is strongly $\mathsf{NP}$-hard. By explicitly constructing quantum circuits whose training objectives reproduce these hard instances, we obtain a polynomial-time reduction to VQA training. Our results establish a fundamental computational barrier to variational quantum training: even reaching the vicinity of a local minimum remains hard in the worst case.

Authors: Dax Enshan Koh, Triscia Mundo, Iosif Sakos, Antonios Varvitsiotis

Variational quantum algorithms (VQAs) generally rely on classical optimization to train parameterized quantum circuits. This training seeks to minimize an objective function, and its efficiency is central to the practical success of these algorithms. However, globally minimizing such training objectives over the circuit parameters is known to be $\mathsf{NP}$-hard, limiting the prospect of general guarantees for efficient training. In this Letter, we prove that even the weaker task of finding a local minimum of such VQA training objectives is strongly $\mathsf{NP}$-hard, including when the objective admits efficient classical evaluation. Moreover, we show that this hardness persists even for the task of finding a parameter vector within $\ell_p$-distance strictly less than $π/2$ of some local minimizer, for every $p\geq 1$. Our central technical result is that approximating a local minimizer of a Hermitian trigonometric polynomial is strongly $\mathsf{NP}$-hard. By explicitly constructing quantum circuits whose training objectives reproduce these hard instances, we obtain a polynomial-time reduction to VQA training. Our results establish a fundamental computational barrier to variational quantum training: even reaching the vicinity of a local minimum remains hard in the worst case.

Tuesday, October 06 2026, 00:00

Gap Amplification for Local Hamiltonians with Combinatorial Soundness

Authors: Mitali Bafna, Quynh T. Nguyen, Tina Zhang

The quantum PCP conjecture is one of the major open problems in quantum complexity theory. It has resisted attack in part because many primitives used in the proof of the classical PCP theorem, such as locality-preserving gap amplification and alphabet reduction, have no obvious quantum analogues due to quantum no-cloning. Locality-preserving gap amplification is a procedure that takes as input a local Hamiltonian problem instance and produces a new instance with a larger promise gap, without increasing the locality of the Hamiltonian, and instead moderately increasing its local qudit dimension. Obtaining this kind of control over the locality during gap amplification is critical to the success of many known strategies for proving the classical PCP theorem. In this work, we put forth the first known viable template for quantum locality-preserving gap amplification, and we prove that our procedure amplifies the combinatorial gap of local Hamiltonians. Our work introduces a new framework for reasoning about quantum gap amplification in terms of fault-tolerant computation, and illuminates a route toward importing one of the central ingredients in classical PCPs into the quantum setting. In particular, we build upon ideas from the recent classical PCP of Bafna--Minzer--Vyas based on high-dimensional expanders, and the circuit-to-Hamiltonian construction of Anshu--Breuckmann--Nguyen, in addition to several recent advances in quantum coding theory.

Authors: Mitali Bafna, Quynh T. Nguyen, Tina Zhang

The quantum PCP conjecture is one of the major open problems in quantum complexity theory. It has resisted attack in part because many primitives used in the proof of the classical PCP theorem, such as locality-preserving gap amplification and alphabet reduction, have no obvious quantum analogues due to quantum no-cloning. Locality-preserving gap amplification is a procedure that takes as input a local Hamiltonian problem instance and produces a new instance with a larger promise gap, without increasing the locality of the Hamiltonian, and instead moderately increasing its local qudit dimension. Obtaining this kind of control over the locality during gap amplification is critical to the success of many known strategies for proving the classical PCP theorem. In this work, we put forth the first known viable template for quantum locality-preserving gap amplification, and we prove that our procedure amplifies the combinatorial gap of local Hamiltonians. Our work introduces a new framework for reasoning about quantum gap amplification in terms of fault-tolerant computation, and illuminates a route toward importing one of the central ingredients in classical PCPs into the quantum setting. In particular, we build upon ideas from the recent classical PCP of Bafna--Minzer--Vyas based on high-dimensional expanders, and the circuit-to-Hamiltonian construction of Anshu--Breuckmann--Nguyen, in addition to several recent advances in quantum coding theory.

Tuesday, October 06 2026, 00:00

Group Action and Spin Representation Lead to a Holant* Complexity Dichotomy on Domain Size 3

Authors: Jin-Yi Cai, Jin Soo Ihm

We prove a complexity dichotomy theorem for $\mathrm{Holant}^*$ problems over complex-valued symmetric constraint functions $\mathcal{F}$ on domain size $3$. We give a decidable tractability criterion and prove that if $\mathcal{F}$ satisfies the criterion, then $\mathrm{Holant}^*(\mathcal{F})$ is solvable in polynomial time, and otherwise it is #P-hard. This is the first Holant dichotomy for a set of complex-valued constraint functions on higher domains. We show that complex-valued constraint functions have a rich structure not observed in real-valued constraint functions. This structure is only revealed when we analyze them in a bipartite Holant setting with a non-standard bilinear form and provides the backbone to the proof of the dichotomy. We use group actions and the spin representation of $\mathrm{SL}(2, \mathbb{C})$ in $\mathrm{SO}(3, \mathbb{C})$ and the generalized orthogonal group to facilitate this analysis. We also introduce $\textit{frames}$ and $\textit{shells}$. Frames linearize the group action and provide a unified framework for proving #P-hardness when used in conjunction with shells. Furthermore, we characterize the lower dimensional constraint functions by $\textit{annihilators}$, which makes it possible to analyze $\textit{essentially Boolean domain}$ functions in domain size $3$.

Authors: Jin-Yi Cai, Jin Soo Ihm

We prove a complexity dichotomy theorem for $\mathrm{Holant}^*$ problems over complex-valued symmetric constraint functions $\mathcal{F}$ on domain size $3$. We give a decidable tractability criterion and prove that if $\mathcal{F}$ satisfies the criterion, then $\mathrm{Holant}^*(\mathcal{F})$ is solvable in polynomial time, and otherwise it is #P-hard. This is the first Holant dichotomy for a set of complex-valued constraint functions on higher domains. We show that complex-valued constraint functions have a rich structure not observed in real-valued constraint functions. This structure is only revealed when we analyze them in a bipartite Holant setting with a non-standard bilinear form and provides the backbone to the proof of the dichotomy. We use group actions and the spin representation of $\mathrm{SL}(2, \mathbb{C})$ in $\mathrm{SO}(3, \mathbb{C})$ and the generalized orthogonal group to facilitate this analysis. We also introduce $\textit{frames}$ and $\textit{shells}$. Frames linearize the group action and provide a unified framework for proving #P-hardness when used in conjunction with shells. Furthermore, we characterize the lower dimensional constraint functions by $\textit{annihilators}$, which makes it possible to analyze $\textit{essentially Boolean domain}$ functions in domain size $3$.

Tuesday, October 06 2026, 00:00

A Fine-Grained Dichotomy for Bounded-Variable Query Evaluation: The Calculus of Relations, a Boolean Modal Logic, and One-Variable Counting Logic

Authors: Yoshiki Nakamura, Yuya Uezato

We study the fine-grained complexity of evaluating Boolean bounded-variable first-order queries over sparse relational structures. For every fixed $k \ge 2$, every relational signature, and every fragment between $k$-variable primitive positive ($\mathrm{PP}^{k}$) and first-order ($\mathrm{FO}^{k}$) logic, we prove, assuming the Sparse MAX-$3$-SAT hypothesis, a dichotomy theorem for evaluation in $O(m^{k-\varepsilon})$ time, where $m$ is the number of tuples in the input structure. The only tractable cases fall into three families: (1) three-variable fragments, (2) two-variable fragments, and (3) fragments over unary signatures. On the hard side, for every fixed $k \ge 4$ and every $\varepsilon > 0$, there is a fixed sentence $\varphi_\varepsilon$ in $\mathrm{PP}^{k}$ over a single binary relation symbol, depending on $\varepsilon$ but not on the input structure, whose evaluation cannot be performed in $O(m^{k-\varepsilon})$ time. For the tractable cases, we show that the evaluation problem can be solved in $2^{O(|\varphi|)} \cdot m^{k-\varepsilon}$ time for some $\varepsilon > 0$. Moreover, every tractable fragment reduces, with a $2^{O(|\varphi|)}$ blowup in formula size under DAG representations, to one of the following query languages: (1) Tarski's calculus of relations, (2) a new Boolean modal logic for sparse model checking, and (3) one-variable counting logic.

Authors: Yoshiki Nakamura, Yuya Uezato

We study the fine-grained complexity of evaluating Boolean bounded-variable first-order queries over sparse relational structures. For every fixed $k \ge 2$, every relational signature, and every fragment between $k$-variable primitive positive ($\mathrm{PP}^{k}$) and first-order ($\mathrm{FO}^{k}$) logic, we prove, assuming the Sparse MAX-$3$-SAT hypothesis, a dichotomy theorem for evaluation in $O(m^{k-\varepsilon})$ time, where $m$ is the number of tuples in the input structure. The only tractable cases fall into three families: (1) three-variable fragments, (2) two-variable fragments, and (3) fragments over unary signatures. On the hard side, for every fixed $k \ge 4$ and every $\varepsilon > 0$, there is a fixed sentence $\varphi_\varepsilon$ in $\mathrm{PP}^{k}$ over a single binary relation symbol, depending on $\varepsilon$ but not on the input structure, whose evaluation cannot be performed in $O(m^{k-\varepsilon})$ time. For the tractable cases, we show that the evaluation problem can be solved in $2^{O(|\varphi|)} \cdot m^{k-\varepsilon}$ time for some $\varepsilon > 0$. Moreover, every tractable fragment reduces, with a $2^{O(|\varphi|)}$ blowup in formula size under DAG representations, to one of the following query languages: (1) Tarski's calculus of relations, (2) a new Boolean modal logic for sparse model checking, and (3) one-variable counting logic.

Tuesday, October 06 2026, 00:00

Strictly Unfriendly $k$-Partitions: Sharp Degree Thresholds and ETH-Based Lower Bounds

Authors: Sanjay Jain, Frank Stephan, Haoyun Tang

We present a complete complexity classification and fine-grained analysis for the Strictly Unfriendly $k$-Partition problem ($\text{SU}k\text{P}$), which asks whether the vertices of a graph can be partitioned into $k$ classes such that every vertex has strictly more neighbors in each of the other $k-1$ classes than in its own. We first establish a sharp tractability-intractability threshold with respect to the maximum degree $Δ$: for $k \in \{2, 3\}$, $\text{SU}k\text{P}$ is solvable in polynomial time when $Δ\le 2$, but becomes $\mathbf{NP}$-hard and ETH-hard immediately on subcubic graphs ($Δ= 3$), resolving the degree limitations in prior work and establishing subcubic graphs as the precise frontier of intractability. Furthermore, under the Exponential Time Hypothesis (ETH), we establish the first fine-grained lower bounds via direct reductions from $(3,3)$-SAT. On general graphs, we establish a uniform lower bound across all partition parameters $k \ge 2$, revealing a striking complexity convergence where the core exponential complexity remains invariant despite technical divergences in gadget constructions. On subcubic graphs, we formally quantify the "cost of sparsity," deriving explicit lower bound constants to demonstrate how enforced structural degree restrictions degrade reduction efficiency.

Authors: Sanjay Jain, Frank Stephan, Haoyun Tang

We present a complete complexity classification and fine-grained analysis for the Strictly Unfriendly $k$-Partition problem ($\text{SU}k\text{P}$), which asks whether the vertices of a graph can be partitioned into $k$ classes such that every vertex has strictly more neighbors in each of the other $k-1$ classes than in its own. We first establish a sharp tractability-intractability threshold with respect to the maximum degree $Δ$: for $k \in \{2, 3\}$, $\text{SU}k\text{P}$ is solvable in polynomial time when $Δ\le 2$, but becomes $\mathbf{NP}$-hard and ETH-hard immediately on subcubic graphs ($Δ= 3$), resolving the degree limitations in prior work and establishing subcubic graphs as the precise frontier of intractability. Furthermore, under the Exponential Time Hypothesis (ETH), we establish the first fine-grained lower bounds via direct reductions from $(3,3)$-SAT. On general graphs, we establish a uniform lower bound across all partition parameters $k \ge 2$, revealing a striking complexity convergence where the core exponential complexity remains invariant despite technical divergences in gadget constructions. On subcubic graphs, we formally quantify the "cost of sparsity," deriving explicit lower bound constants to demonstrate how enforced structural degree restrictions degrade reduction efficiency.

Tuesday, October 06 2026, 00:00

Nonuniform QCPH Collapse Implies QCPH Collapse

Authors: Jeremy Ahrens Huang

Despite the importance of the non-uniform Polynomial-Time Hierarchy (PH/poly) in classical complexity understanding the collapse conditions of the Polynomial-Time Hierarchy (PH), a quantum equivalent of PH/poly has yet to be studied in the literature. We introduce the non-uniform computational Quantum Polynomial-Time Hierarchy (QCPH/mpoly), the quantum equivalent of PH/poly, and show that it collapses if and only if QCPH, the quantum equivalent of PH introduced by Gharibian et al. (comput. complex. 2022), also collapses. We also show that QCPH collapses if coQCMA is contained in QCMA/mpoly. These results are analogous to those of Yap (TCS 1983) commonly used to invoke the collapse of PH in classical complexity. QCPH/mpoly is analogous to QCPH with non-uniform quantum verifier circuits.

Authors: Jeremy Ahrens Huang

Despite the importance of the non-uniform Polynomial-Time Hierarchy (PH/poly) in classical complexity understanding the collapse conditions of the Polynomial-Time Hierarchy (PH), a quantum equivalent of PH/poly has yet to be studied in the literature. We introduce the non-uniform computational Quantum Polynomial-Time Hierarchy (QCPH/mpoly), the quantum equivalent of PH/poly, and show that it collapses if and only if QCPH, the quantum equivalent of PH introduced by Gharibian et al. (comput. complex. 2022), also collapses. We also show that QCPH collapses if coQCMA is contained in QCMA/mpoly. These results are analogous to those of Yap (TCS 1983) commonly used to invoke the collapse of PH in classical complexity. QCPH/mpoly is analogous to QCPH with non-uniform quantum verifier circuits.

Tuesday, October 06 2026, 00:00

A Hand-Checkable Proof That Two Hidden ReLU Layers Compute the Maximum of Six Numbers

Authors: Dimitrios Myrisiotis

Exactly computing the maximum function is a standard test case for studying depth in ReLU networks. Two hidden layers are known to suffice for up to twelve inputs through computer-assisted constructions. For six real inputs, we give an explicit hexagon identity whose local structure yields a self-contained analytical proof of this depth bound. The identity was found by computer-assisted search; we prove it through explicit cancellations that can be checked entirely by hand, without executing a verification program. The identity also yields an explicit network with hidden widths $17$ and $41$, zero biases, and rational weights.

Authors: Dimitrios Myrisiotis

Exactly computing the maximum function is a standard test case for studying depth in ReLU networks. Two hidden layers are known to suffice for up to twelve inputs through computer-assisted constructions. For six real inputs, we give an explicit hexagon identity whose local structure yields a self-contained analytical proof of this depth bound. The identity was found by computer-assisted search; we prove it through explicit cancellations that can be checked entirely by hand, without executing a verification program. The identity also yields an explicit network with hidden widths $17$ and $41$, zero biases, and rational weights.

Tuesday, October 06 2026, 00:00

Black Hole Radiation Decoding in the Haar Random Oracle Model

Authors: Ezekiel Cochran, Atul Mantri

We prove optimal query bounds for recovering a single qubit from black-hole radiation in the Haar random oracle model, when the remaining black hole contains at most one sixteenth of the system's qubits. Recovery with any constant Haar-averaged advantage over trivial decoding requires queries proportional to the Hilbert-space dimension of the remaining black hole. The lower bound is unconditional for decoders chosen independently of the sampled unitary, allows arbitrary computation between queries, and access to $U, U^\dagger, U^*, U^\mathsf T$ along with the controlled variants. An existing decoder using only forward and inverse queries attains a matching bound. The proof uses a path recording oracle to compare real and maximally mixed states. As applications, we obtain an efficiently preparable, statistically far, computationally indistinguishable (EFI) pair and quantum commitments relative to a public Haar oracle, as well as prove a tight linear rank lower bound for Uhlmann transformation on a fixed-target family.

Authors: Ezekiel Cochran, Atul Mantri

We prove optimal query bounds for recovering a single qubit from black-hole radiation in the Haar random oracle model, when the remaining black hole contains at most one sixteenth of the system's qubits. Recovery with any constant Haar-averaged advantage over trivial decoding requires queries proportional to the Hilbert-space dimension of the remaining black hole. The lower bound is unconditional for decoders chosen independently of the sampled unitary, allows arbitrary computation between queries, and access to $U, U^\dagger, U^*, U^\mathsf T$ along with the controlled variants. An existing decoder using only forward and inverse queries attains a matching bound. The proof uses a path recording oracle to compare real and maximally mixed states. As applications, we obtain an efficiently preparable, statistically far, computationally indistinguishable (EFI) pair and quantum commitments relative to a public Haar oracle, as well as prove a tight linear rank lower bound for Uhlmann transformation on a fixed-target family.

Tuesday, October 06 2026, 00:00

An Analysis of Decision Problems for Relational Pattern Languages under Various Constraints

Authors: Klaus Jansen, Dirk Nowotka, Lis Pirotton, Corinna Wambsganz, Max Wiedenhöft

Patterns are words with terminals and variables. The language of a pattern is the set of words obtained by uniformly substituting all variables with words that contain only terminals. In their original definition, patterns only allow for multiple distinct occurrences of some variables to be related by the equality relation, represented by using the same variable multiple times. In an extended notion, called relational patterns and relational pattern languages, variables may be related by arbitrary other relations, achieved by using regular patterns and relating individual variables independently from the patterns structure separately. We extend the ongoing investigation of the main decision problems for patterns (namely, the equivalence problem, the inclusion problem, and the membership problem) to relational pattern languages under a wide range of relevant individual relations, providing a comprehensive foundation in all three research directions.

Authors: Klaus Jansen, Dirk Nowotka, Lis Pirotton, Corinna Wambsganz, Max Wiedenhöft

Patterns are words with terminals and variables. The language of a pattern is the set of words obtained by uniformly substituting all variables with words that contain only terminals. In their original definition, patterns only allow for multiple distinct occurrences of some variables to be related by the equality relation, represented by using the same variable multiple times. In an extended notion, called relational patterns and relational pattern languages, variables may be related by arbitrary other relations, achieved by using regular patterns and relating individual variables independently from the patterns structure separately. We extend the ongoing investigation of the main decision problems for patterns (namely, the equivalence problem, the inclusion problem, and the membership problem) to relational pattern languages under a wide range of relevant individual relations, providing a comprehensive foundation in all three research directions.

Tuesday, October 06 2026, 00:00

Min-Max Uniform Circle Formation by Asynchronous Mobile Robots

Authors: Animesh Maiti, Prakhar Shukla, Subhash Bhagat

Given a set of point robots $\mathcal{R}$ in the Euclidean plane and a target circle $\mathbf C$ enclosing all robot positions, the \textsc{Min-Max Uniform Circle Formation (MMUCF)} problem requires the robots to move to distinct positions on $\mathbf C$ such that the final configuration forms a regular $n$-gon while minimizing the maximum distance traveled by any robot. Uniform circle formation is a fundamental coordination task in swarm robotics with applications in perimeter monitoring, surveillance, boundary coverage, and pattern formation. The literature does not address the optimization of the maximum individual displacement during the formation process. In this work, we study the min--max versions of the circle formation and uniform circle formation problems, where the goal is to minimize the maximum distance traveled by any robot. We consider these problems under the $\mathcal{ASYNC}$ model, where robots are autonomous, anonymous, identical, homogeneous, oblivious, and silent, and operate under the \textit{Look--Compute--Move} model with non-rigid motion. We first give necessary conditions for a deterministic solution and then present deterministic, distributed, and collision-free algorithms that form a circle and a uniform circle in finite time while minimizing the maximum movement. The algorithms ensure that robots reach distinct positions on the circle and, in the uniform case, equally spaced positions on $\mathbf C$ under the considered model.

Authors: Animesh Maiti, Prakhar Shukla, Subhash Bhagat

Given a set of point robots $\mathcal{R}$ in the Euclidean plane and a target circle $\mathbf C$ enclosing all robot positions, the \textsc{Min-Max Uniform Circle Formation (MMUCF)} problem requires the robots to move to distinct positions on $\mathbf C$ such that the final configuration forms a regular $n$-gon while minimizing the maximum distance traveled by any robot. Uniform circle formation is a fundamental coordination task in swarm robotics with applications in perimeter monitoring, surveillance, boundary coverage, and pattern formation. The literature does not address the optimization of the maximum individual displacement during the formation process. In this work, we study the min--max versions of the circle formation and uniform circle formation problems, where the goal is to minimize the maximum distance traveled by any robot. We consider these problems under the $\mathcal{ASYNC}$ model, where robots are autonomous, anonymous, identical, homogeneous, oblivious, and silent, and operate under the \textit{Look--Compute--Move} model with non-rigid motion. We first give necessary conditions for a deterministic solution and then present deterministic, distributed, and collision-free algorithms that form a circle and a uniform circle in finite time while minimizing the maximum movement. The algorithms ensure that robots reach distinct positions on the circle and, in the uniform case, equally spaced positions on $\mathbf C$ under the considered model.

Tuesday, October 06 2026, 00:00

Budget-Constrained Fault-Tolerant Mutual Visibility for Autonomous Robots under the Mobility Fault Model

Authors: Prakhar Shukla, Animesh Maiti, Shivam Kumar, Subhash Bhagat

We investigate the mutual visibility problem for a swarm of $n\ge3$ autonomous mobile robots under the budget-constrained mobility fault model. The robots are opaque, so if three robots are collinear, the middle robot obstructs the visibility between the other two. Each robot is assigned a finite movement budget, reflecting its limited energy, that bounds the total distance it may traverse during the execution. Moreover, an arbitrary number of robots may become permanently immobile due to mobility faults. The objective is to design a distributed algorithm that enables the non-faulty robots to coordinate their movements so that, within a finite time, every non-faulty robot attains unobstructed visibility of all robots in the system, including the faulty ones, while respecting the prescribed movement budget. We consider luminous robots operating under the $\mathsf{SSYNC}$ model with non-rigid movements, without any agreement on their local coordinate systems, and equipped only with a {\it common fixed reference point}. We present a deterministic distributed algorithm that solves the problem despite an arbitrary number of mobility faults. The algorithm guarantees mutual visibility for the non-faulty robots, respects the movement budget of every robot, provides collision-free movements for the robots, and uses only 12 light colors.

Authors: Prakhar Shukla, Animesh Maiti, Shivam Kumar, Subhash Bhagat

We investigate the mutual visibility problem for a swarm of $n\ge3$ autonomous mobile robots under the budget-constrained mobility fault model. The robots are opaque, so if three robots are collinear, the middle robot obstructs the visibility between the other two. Each robot is assigned a finite movement budget, reflecting its limited energy, that bounds the total distance it may traverse during the execution. Moreover, an arbitrary number of robots may become permanently immobile due to mobility faults. The objective is to design a distributed algorithm that enables the non-faulty robots to coordinate their movements so that, within a finite time, every non-faulty robot attains unobstructed visibility of all robots in the system, including the faulty ones, while respecting the prescribed movement budget. We consider luminous robots operating under the $\mathsf{SSYNC}$ model with non-rigid movements, without any agreement on their local coordinate systems, and equipped only with a {\it common fixed reference point}. We present a deterministic distributed algorithm that solves the problem despite an arbitrary number of mobility faults. The algorithm guarantees mutual visibility for the non-faulty robots, respects the movement budget of every robot, provides collision-free movements for the robots, and uses only 12 light colors.

Tuesday, October 06 2026, 00:00

Adaptive Bregman Alternating Projections for Feasible Gromov-Wasserstein Learning

Authors: Aoran Zhang, César A. Uribe

The Gromov-Wasserstein (GW) problem compares structured distributions without requiring a shared feature space or known correspondences, but its nonconvex objective and coupled marginal constraints make computation challenging. Bregman alternating projected gradient (BAPG) uses inexpensive alternating row and column updates, yet its fixed-penalty relaxation leaves a persistent feasibility gap. We propose Adaptive KL-BAPG (A-KL-BAPG), which combines a finite fixed-penalty burn-in with a guarded increasing-penalty phase. At each tail iteration, the method reuses BAPG's alternating updates and backtracks a delayed-power step until a Sinkhorn-inspired projective-diameter safeguard is satisfied. We prove finite termination of the backtracking at each iteration and show that the feasibility gap vanishes asymptotically. We further establish a best-iterate $O(1/\log N)$ bound for the weighted squared corrected residual and, under a support regularity condition, the existence of a stationary accumulation point for the original GW problem. This distinguishes A-KL-BAPG from fixed-penalty BAPG, whose stationarity guarantees are given for the relaxed problem. Experiments show that A-KL-BAPG achieves a favorable balance of accuracy, objective value, feasibility, and stationarity relative to BAPG variants, projection-based methods, and task-specific baselines. For synthetic and real graph alignment problems, it closely matches the accuracy and objective value of fixed-penalty KL-BAPG while reducing the marginal feasibility gap by 62-99% and the projected stationarity residual by 28-98%. Heterogeneous domain adaptation experiments show a similar pattern: A-KL-BAPG maintains comparable target accuracy and objective values while achieving better feasibility and stationarity than fixed-penalty KL-BAPG.

Authors: Aoran Zhang, César A. Uribe

The Gromov-Wasserstein (GW) problem compares structured distributions without requiring a shared feature space or known correspondences, but its nonconvex objective and coupled marginal constraints make computation challenging. Bregman alternating projected gradient (BAPG) uses inexpensive alternating row and column updates, yet its fixed-penalty relaxation leaves a persistent feasibility gap. We propose Adaptive KL-BAPG (A-KL-BAPG), which combines a finite fixed-penalty burn-in with a guarded increasing-penalty phase. At each tail iteration, the method reuses BAPG's alternating updates and backtracks a delayed-power step until a Sinkhorn-inspired projective-diameter safeguard is satisfied. We prove finite termination of the backtracking at each iteration and show that the feasibility gap vanishes asymptotically. We further establish a best-iterate $O(1/\log N)$ bound for the weighted squared corrected residual and, under a support regularity condition, the existence of a stationary accumulation point for the original GW problem. This distinguishes A-KL-BAPG from fixed-penalty BAPG, whose stationarity guarantees are given for the relaxed problem. Experiments show that A-KL-BAPG achieves a favorable balance of accuracy, objective value, feasibility, and stationarity relative to BAPG variants, projection-based methods, and task-specific baselines. For synthetic and real graph alignment problems, it closely matches the accuracy and objective value of fixed-penalty KL-BAPG while reducing the marginal feasibility gap by 62-99% and the projected stationarity residual by 28-98%. Heterogeneous domain adaptation experiments show a similar pattern: A-KL-BAPG maintains comparable target accuracy and objective values while achieving better feasibility and stationarity than fixed-penalty KL-BAPG.

Tuesday, October 06 2026, 00:00

When Robots Crash: Optimal Asynchronous Gathering at Weber Meeting Nodes

Authors: Animesh Maiti, Prakhar Shukla, Abhinav Chakraborty, Subhash Bhagat

We study the \textit{optimal gathering} problem over a finite set of designated \textit{meeting nodes} for \textit{asynchronous, anonymous,} and \textit{oblivious} mobile robots on an infinite grid under crash faults. The robots have global visibility and strong multiplicity detection, but share neither a coordinate system nor chirality. The objective is to gather all non-faulty robots at a \textsc{Weber Meeting Node}, minimizing the total Manhattan distance from their initial positions. Up to $n-2$ robots may crash permanently, and such crashes are indistinguishable from arbitrary delays. Existing approaches often rely on a designated robot to break symmetry, whose crash may block the remaining robots indefinitely. Instead, our approach enables every robot to independently select the same target from its snapshot, while target-dependent restricted shortest paths preserve the target as a \textsc{Weber Meeting Node}. We prove that, under strong multiplicity detection, optimal gathering is impossible from certain fully symmetric configurations. For all remaining configurations, our algorithm \textsc{CrashTolerantWeberGathering()} selects a unique common target, preserves its optimality throughout the execution, and allows non-faulty robots to progress without waiting for crashed robots, thereby guaranteeing gathering in finite time.

Authors: Animesh Maiti, Prakhar Shukla, Abhinav Chakraborty, Subhash Bhagat

We study the \textit{optimal gathering} problem over a finite set of designated \textit{meeting nodes} for \textit{asynchronous, anonymous,} and \textit{oblivious} mobile robots on an infinite grid under crash faults. The robots have global visibility and strong multiplicity detection, but share neither a coordinate system nor chirality. The objective is to gather all non-faulty robots at a \textsc{Weber Meeting Node}, minimizing the total Manhattan distance from their initial positions. Up to $n-2$ robots may crash permanently, and such crashes are indistinguishable from arbitrary delays. Existing approaches often rely on a designated robot to break symmetry, whose crash may block the remaining robots indefinitely. Instead, our approach enables every robot to independently select the same target from its snapshot, while target-dependent restricted shortest paths preserve the target as a \textsc{Weber Meeting Node}. We prove that, under strong multiplicity detection, optimal gathering is impossible from certain fully symmetric configurations. For all remaining configurations, our algorithm \textsc{CrashTolerantWeberGathering()} selects a unique common target, preserves its optimality throughout the execution, and allows non-faulty robots to progress without waiting for crashed robots, thereby guaranteeing gathering in finite time.

Tuesday, October 06 2026, 00:00

Truly Subquadratic 3SUM and Truly Subcubic APSP via Triangles in Sparse Lopsided Graphs

Authors: Josh Alman, Virginia Vassilevska Williams

We give the first polynomial improvements over the textbook algorithms for $3$SUM and All-Pairs Shortest Paths (APSP): we show how to deterministically solve $3$SUM on $n$ integers of polynomial size in $O(n^{1.9992})$ time and APSP on directed $n$-vertex graphs with polynomially bounded integer weights in $O(n^{2.9995})$ time. This refutes the $3$SUM and APSP hypotheses. Using known reductions, we also refute the real-valued versions of the $3$SUM and APSP hypotheses, the Exact Triangle hypothesis, the Zero-Weight $k$-Clique hypotheses, and the three rectangular hinted Online Matrix--Vector conjectures of van den Brand, Nanongkai, and Saranurak, and we give polynomial speedups for a variety of other problems. All of these results follow from a single new algorithm for thin matrix products. Let $X$ be an $N\times D$ integer matrix and $Y$ a $D\times N$ integer matrix with $D\le N^{1/18}$, and let $W$ be any set of at most $N^2/\sqrt D$ positions. We compute the entries $(XY)[I,J]$, $(I,J)\in W$, in $O(N^2/D^{0.063})$ operations, which is polynomially less than the time needed to write down $XY$ or to compute $N^2/\sqrt D$ inner products one by one. We design this algorithm by modifying a variant of Coppersmith's rectangular matrix multiplication algorithm, built from a ten-multiplication identity of Schönhage, to perform only the operations needed for the entries in $W$, and show that few operations are needed. Interpreted as a graph algorithm, this solves the All-Edges Sparse Triangle problem in truly subquadratic time on sparse lopsided tripartite graphs where two parts have $n$ vertices but one part has $n^{\varepsilon}$ vertices for $\varepsilon<0.12$. By known reductions, Exact Triangle, and hence $3$SUM and APSP, reduce to this problem. We also give a data structure version that answers queries for single entries of $XY$, not known in advance.

Authors: Josh Alman, Virginia Vassilevska Williams

We give the first polynomial improvements over the textbook algorithms for $3$SUM and All-Pairs Shortest Paths (APSP): we show how to deterministically solve $3$SUM on $n$ integers of polynomial size in $O(n^{1.9992})$ time and APSP on directed $n$-vertex graphs with polynomially bounded integer weights in $O(n^{2.9995})$ time. This refutes the $3$SUM and APSP hypotheses. Using known reductions, we also refute the real-valued versions of the $3$SUM and APSP hypotheses, the Exact Triangle hypothesis, the Zero-Weight $k$-Clique hypotheses, and the three rectangular hinted Online Matrix--Vector conjectures of van den Brand, Nanongkai, and Saranurak, and we give polynomial speedups for a variety of other problems. All of these results follow from a single new algorithm for thin matrix products. Let $X$ be an $N\times D$ integer matrix and $Y$ a $D\times N$ integer matrix with $D\le N^{1/18}$, and let $W$ be any set of at most $N^2/\sqrt D$ positions. We compute the entries $(XY)[I,J]$, $(I,J)\in W$, in $O(N^2/D^{0.063})$ operations, which is polynomially less than the time needed to write down $XY$ or to compute $N^2/\sqrt D$ inner products one by one. We design this algorithm by modifying a variant of Coppersmith's rectangular matrix multiplication algorithm, built from a ten-multiplication identity of Schönhage, to perform only the operations needed for the entries in $W$, and show that few operations are needed. Interpreted as a graph algorithm, this solves the All-Edges Sparse Triangle problem in truly subquadratic time on sparse lopsided tripartite graphs where two parts have $n$ vertices but one part has $n^{\varepsilon}$ vertices for $\varepsilon<0.12$. By known reductions, Exact Triangle, and hence $3$SUM and APSP, reduce to this problem. We also give a data structure version that answers queries for single entries of $XY$, not known in advance.

Tuesday, October 06 2026, 00:00

An FPRAS for Counting Common Bases of Two Matroids

Authors: Xiaoyu Chen, Kuikui Liu

We design the first polynomial-time algorithms for approximately counting and almost uniformly sampling common bases of two matroids given by their independence oracles. Moreover, our algorithms generalize far beyond this to Hadamard products of two probability measures on the Boolean cube satisfying a simple nonnegative curvature condition. These algorithmic primitives have myriad applications in statistical physics, polyhedral combinatorics, the study of quantum many-body systems, and beyond. Our approach has two key ingredients. $\bullet$ We relax the intersection by imposing an overlap penalty on the product measure formed by the two input measures. We prove, via an integrated Bochner-type method, that this "$\textit{soft intersection}$" satisfies a Poincare inequality uniformly over all external fields. $\bullet$ We solve a dual maximum entropy convex program to compute external fields under which the hard constraint is satisfied with high probability under the soft intersection measure. We bound this success probability directly using the uniform Poincare inequality and smallness of the gradient norm. $\textbf{AI Disclosure}$ GPT-5.6 Sol Ultra and GPT-6 Astra Ultra were heavily used to develop the ideas in this paper. A more complete discussion is included in the acknowledgments.

Authors: Xiaoyu Chen, Kuikui Liu

We design the first polynomial-time algorithms for approximately counting and almost uniformly sampling common bases of two matroids given by their independence oracles. Moreover, our algorithms generalize far beyond this to Hadamard products of two probability measures on the Boolean cube satisfying a simple nonnegative curvature condition. These algorithmic primitives have myriad applications in statistical physics, polyhedral combinatorics, the study of quantum many-body systems, and beyond. Our approach has two key ingredients. $\bullet$ We relax the intersection by imposing an overlap penalty on the product measure formed by the two input measures. We prove, via an integrated Bochner-type method, that this "$\textit{soft intersection}$" satisfies a Poincare inequality uniformly over all external fields. $\bullet$ We solve a dual maximum entropy convex program to compute external fields under which the hard constraint is satisfied with high probability under the soft intersection measure. We bound this success probability directly using the uniform Poincare inequality and smallness of the gradient norm. $\textbf{AI Disclosure}$ GPT-5.6 Sol Ultra and GPT-6 Astra Ultra were heavily used to develop the ideas in this paper. A more complete discussion is included in the acknowledgments.

Tuesday, October 06 2026, 00:00

A Uniform Algorithm for Strict NP on Bounded-Treedepth Graphs

Authors: Thomas Depian, Robert Ganian, Jakob Greilhuber, Marlene Gründel, Simon Wietheger

A classical well-quasi-ordering result guarantees the existence of non-uniform linear-time algorithms for all problems in Strict NP on relational structures of bounded treedepth; however, this provides neither a procedure for constructing these algorithms nor computable bounds on their parameter dependence. We turn this existential result into a uniform algorithmic metatheorem. Given a Strict NP sentence $\varphi$ and a relational structure $\mathcal{R}$, our algorithm decides whether $\mathcal{R}\models\varphi$ in time $f(|\varphi|, td(\mathcal{R})) \cdot |\mathcal{R}|$ for a computable function $f$, where the treedepth of $\mathcal{R}$ is measured on the Gaifman graph. The algorithm also constructs witness relations, with the polynomial exponent depending on their arity, and provides a unified framework for settling hereditary graph problems parameterized by treedepth. We also present several applications - among others, our result resolves open questions on the fixed-parameter tractability of computing the stack number, queue number, track number and twin-width parameterized by treedepth.

Authors: Thomas Depian, Robert Ganian, Jakob Greilhuber, Marlene Gründel, Simon Wietheger

A classical well-quasi-ordering result guarantees the existence of non-uniform linear-time algorithms for all problems in Strict NP on relational structures of bounded treedepth; however, this provides neither a procedure for constructing these algorithms nor computable bounds on their parameter dependence. We turn this existential result into a uniform algorithmic metatheorem. Given a Strict NP sentence $\varphi$ and a relational structure $\mathcal{R}$, our algorithm decides whether $\mathcal{R}\models\varphi$ in time $f(|\varphi|, td(\mathcal{R})) \cdot |\mathcal{R}|$ for a computable function $f$, where the treedepth of $\mathcal{R}$ is measured on the Gaifman graph. The algorithm also constructs witness relations, with the polynomial exponent depending on their arity, and provides a unified framework for settling hereditary graph problems parameterized by treedepth. We also present several applications - among others, our result resolves open questions on the fixed-parameter tractability of computing the stack number, queue number, track number and twin-width parameterized by treedepth.

Tuesday, October 06 2026, 00:00

Robust subspace designs and the power of a unique small quantum witness

Authors: Simon Apers, Roman Edenhofer, Benjamin Mathieu-Bloise, Partha Mukhopadhyay

The concept of subspace designs was introduced by Guruswami and Xing (STOC'13), and explicit constructions were given by Guruswami and Kopparty (FOCS'13). These are families of subspaces that have small intersection with any given subspace of a fixed dimension. We introduce \emph{robust subspace designs}. Informally, these are a quantitative extension in which we demand that not too many subspaces of the family contain directions that lie close to any given subspace of a fixed dimension. We give a probabilistic construction of such a robust subspace design of polynomial size, as well as a non-trivial explicit construction of superpolynomial size. Our main application of this new concept is a quantum space-bounded variant of the Valiant-Vazirani theorem (Theor.Comput.Sci.'86), which shows that restricting $\mathsf{NP}$-complete problems to instances with at most one accepting witness preserves hardness under randomized reductions. For quantum witnesses, the analogous quantity is the dimension of an accepting witness subspace. We use our probabilistic construction of robust subspace designs to isolate a unique witness for space-bounded quantum Merlin-Arthur protocols with perfect completeness and an acceptance gap outside their perfectly accepting subspace. As further applications, we give a randomized reduction of well-conditioned nullity testing to space-bounded quantum Merlin-Arthur protocols with perfect completeness. Using a similar idea, we find that ordinary subspace designs allow us to recover the classical $\mathsf{C_= L}$ containment of Allender, Beals, and Ogihara (STOC'96) for general nullity testing through a simpler proof.

Authors: Simon Apers, Roman Edenhofer, Benjamin Mathieu-Bloise, Partha Mukhopadhyay

The concept of subspace designs was introduced by Guruswami and Xing (STOC'13), and explicit constructions were given by Guruswami and Kopparty (FOCS'13). These are families of subspaces that have small intersection with any given subspace of a fixed dimension. We introduce \emph{robust subspace designs}. Informally, these are a quantitative extension in which we demand that not too many subspaces of the family contain directions that lie close to any given subspace of a fixed dimension. We give a probabilistic construction of such a robust subspace design of polynomial size, as well as a non-trivial explicit construction of superpolynomial size. Our main application of this new concept is a quantum space-bounded variant of the Valiant-Vazirani theorem (Theor.Comput.Sci.'86), which shows that restricting $\mathsf{NP}$-complete problems to instances with at most one accepting witness preserves hardness under randomized reductions. For quantum witnesses, the analogous quantity is the dimension of an accepting witness subspace. We use our probabilistic construction of robust subspace designs to isolate a unique witness for space-bounded quantum Merlin-Arthur protocols with perfect completeness and an acceptance gap outside their perfectly accepting subspace. As further applications, we give a randomized reduction of well-conditioned nullity testing to space-bounded quantum Merlin-Arthur protocols with perfect completeness. Using a similar idea, we find that ordinary subspace designs allow us to recover the classical $\mathsf{C_= L}$ containment of Allender, Beals, and Ogihara (STOC'96) for general nullity testing through a simpler proof.

Tuesday, October 06 2026, 00:00

Matching with Multiple Bottlenecks: Parameterized Complexity and Approximation

Authors: Jonas Friemel, Tilo Hoitz, Phillip Keldenich, Arne Schmidt

We consider a matching problem in which the cost of each edge is a vector with $k$ components. The cost of a matching is the sum of the bottlenecks over all components, and we ask whether there is a perfect matching of cost at most some value $Z$. This type of matching has applications in heavily synchronized job-shop scheduling problems and in reconfiguration problems, where movement is restricted to a single direction per step. In this paper, we analyze the problem from a parameterized complexity perspective and provide various results including FPT-membership for parameters $k$ and $Z$ combined, as well as W[P]-membership and W[SAT]-hardness for each of the two parameters individually. The reduction also implies para-NP-hardness parameterized by either maximum degree or treewidth. We further show hardness of approximation within a super-logarithmic factor for the optimization variant and provide a $k/d$-approximation algorithm for any constant $d \leq k$ as well as an efficient approximation scheme parameterized by $k$. With parameter $Z$, we show that no FPT-time $F(Z)$-approximation algorithm is possible for any computable function $F$, unless W[1] = FPT.

Authors: Jonas Friemel, Tilo Hoitz, Phillip Keldenich, Arne Schmidt

We consider a matching problem in which the cost of each edge is a vector with $k$ components. The cost of a matching is the sum of the bottlenecks over all components, and we ask whether there is a perfect matching of cost at most some value $Z$. This type of matching has applications in heavily synchronized job-shop scheduling problems and in reconfiguration problems, where movement is restricted to a single direction per step. In this paper, we analyze the problem from a parameterized complexity perspective and provide various results including FPT-membership for parameters $k$ and $Z$ combined, as well as W[P]-membership and W[SAT]-hardness for each of the two parameters individually. The reduction also implies para-NP-hardness parameterized by either maximum degree or treewidth. We further show hardness of approximation within a super-logarithmic factor for the optimization variant and provide a $k/d$-approximation algorithm for any constant $d \leq k$ as well as an efficient approximation scheme parameterized by $k$. With parameter $Z$, we show that no FPT-time $F(Z)$-approximation algorithm is possible for any computable function $F$, unless W[1] = FPT.

Tuesday, October 06 2026, 00:00

W[1]-Hardness of Upper Clique Transversal

Authors: Pascal J. Gollin, Tesshu Hanaka, Ekkehard Köhler, Martin Milanič, Yushi Uno

A clique transversal of a graph is a set of vertices intersecting every maximal clique. We prove that deciding whether a graph has an inclusion-wise minimal clique transversal of size at least $k$ is W[1]-hard when parameterized by $k$.

Authors: Pascal J. Gollin, Tesshu Hanaka, Ekkehard Köhler, Martin Milanič, Yushi Uno

A clique transversal of a graph is a set of vertices intersecting every maximal clique. We prove that deciding whether a graph has an inclusion-wise minimal clique transversal of size at least $k$ is W[1]-hard when parameterized by $k$.

Tuesday, October 06 2026, 00:00

Quantum Submodular Maximization

Authors: Yonggang Jiang, Xiaoming Sun, Penghui Yao, Zekun Ye, Jialin Zhang, Zhijie Zhang

We study the quantum query complexity of maximizing a non-negative submodular function, considering both the unconstrained setting and, for monotone functions, a cardinality constraint $k$ on an $n$-element ground set. In the exact reversible digital value-oracle model, our unconstrained algorithm achieves an expected $(1/2-\varepsilon)$-approximation using only $O_\varepsilon(\log n)$ queries. In contrast, any classical randomized algorithm that attains a fixed expected ratio above $1/4$ requires $Ω(n/\log n)$ queries (Li, Feldman, Kazemi, and Karbasi, 2022), establishing an exponential separation in query complexity. For cardinality-constrained maximization, we give a bounded-error quantum algorithm that achieves a $(1-1/e-\varepsilon)$-approximation using $\widetilde O_\varepsilon(\min\{\sqrt n,n/k\})$ queries. When $k=o(n)$, our algorithm achieves at least a quadratic speedup up to logarithmic factors over classical randomized algorithms (Mirzasoleiman, Badanidiyuru, Karbasi, Vondrák, and Krause, 2015; Peng and Rubinstein, 2025). Moreover, when $k=cn$ for any fixed rational $c<1-1/e-\varepsilon$, the query complexity reduces to $O_{\varepsilon,c}(\log n)$, yielding an exponential separation from the classical $Ω(n/\log n)$ lower bound (Li, Feldman, Kazemi, and Karbasi, 2022). We further prove quantum lower bounds of $\exp(Ω(\varepsilon^2n))$ queries for achieving a ratio beyond $1/2+\varepsilon$ without constraints, and $\exp(Ω(\varepsilon^2k))$ queries for exceeding $1-1/e+\varepsilon$ when $k/n\le\varepsilon$. These barriers demonstrate that quantum computation offers no exponential speedup at these approximation thresholds.

Authors: Yonggang Jiang, Xiaoming Sun, Penghui Yao, Zekun Ye, Jialin Zhang, Zhijie Zhang

We study the quantum query complexity of maximizing a non-negative submodular function, considering both the unconstrained setting and, for monotone functions, a cardinality constraint $k$ on an $n$-element ground set. In the exact reversible digital value-oracle model, our unconstrained algorithm achieves an expected $(1/2-\varepsilon)$-approximation using only $O_\varepsilon(\log n)$ queries. In contrast, any classical randomized algorithm that attains a fixed expected ratio above $1/4$ requires $Ω(n/\log n)$ queries (Li, Feldman, Kazemi, and Karbasi, 2022), establishing an exponential separation in query complexity. For cardinality-constrained maximization, we give a bounded-error quantum algorithm that achieves a $(1-1/e-\varepsilon)$-approximation using $\widetilde O_\varepsilon(\min\{\sqrt n,n/k\})$ queries. When $k=o(n)$, our algorithm achieves at least a quadratic speedup up to logarithmic factors over classical randomized algorithms (Mirzasoleiman, Badanidiyuru, Karbasi, Vondrák, and Krause, 2015; Peng and Rubinstein, 2025). Moreover, when $k=cn$ for any fixed rational $c<1-1/e-\varepsilon$, the query complexity reduces to $O_{\varepsilon,c}(\log n)$, yielding an exponential separation from the classical $Ω(n/\log n)$ lower bound (Li, Feldman, Kazemi, and Karbasi, 2022). We further prove quantum lower bounds of $\exp(Ω(\varepsilon^2n))$ queries for achieving a ratio beyond $1/2+\varepsilon$ without constraints, and $\exp(Ω(\varepsilon^2k))$ queries for exceeding $1-1/e+\varepsilon$ when $k/n\le\varepsilon$. These barriers demonstrate that quantum computation offers no exponential speedup at these approximation thresholds.

Tuesday, October 06 2026, 00:00

Locality Sensitive Hashing for p-Exponential Kernels with Applications to Density Estimation

Authors: Barak Gorodissky, Tal Wagner

A kernel $k(x,y)$ is LSHable if there exists a locality sensitive hashing scheme $H$ such that $k(x,y)=\Pr_{h\sim H}[h(x)=h(y)]$ for all $x,y$. This notion plays a key role in efficient kernel methods in high dimensions. In this work, we show that the $p$-exponential kernel $k(x,y)=\exp(-\lVert x-y \rVert_p)$ is LSHable in bounded regions for all $1

Authors: Barak Gorodissky, Tal Wagner

A kernel $k(x,y)$ is LSHable if there exists a locality sensitive hashing scheme $H$ such that $k(x,y)=\Pr_{h\sim H}[h(x)=h(y)]$ for all $x,y$. This notion plays a key role in efficient kernel methods in high dimensions. In this work, we show that the $p$-exponential kernel $k(x,y)=\exp(-\lVert x-y \rVert_p)$ is LSHable in bounded regions for all $1

Tuesday, October 06 2026, 00:00

Improved Upper and Lower Bounds for Quantum Convex-Body Volume Estimation

Authors: Ruizhe Zhang

Estimating the volume of a high-dimensional convex body is a fundamental problem in theoretical computer science. Given a quantum membership oracle for a convex body $K\subset\mathbb{R}^d$, we show that estimating $\mathrm{vol}(K)$ to relative error $\varepsilon$ takes $\widetilde O(d^{5/2}+d^{3/2}/\varepsilon)$ queries. This improves the previous quantum upper bound $\widetilde O(d^3+d^{9/4}/\varepsilon)$ of Chakrabarti et al. (ACM TQC 2023) and Cornelissen--Hamoudi (SODA 2023), and achieves a larger quantum speedup over the currently best classical upper bound $\widetilde O(d^{7/2}+d^3/\varepsilon^2)$ of Jia et al. (JACM 2026). Our quantum algorithm combines two new ingredients: an input-dependent effective spectral-gap analysis of quantum walks based on uniform classical warm-start mixing bounds, and a single quantum estimator for products of normalizer ratios in simulated annealing based on classical bridge sampling. We also prove an $Ω(d)$ quantum query lower bound for constant relative error, improving the previous $Ω(\sqrt d)$ lower bound.

Authors: Ruizhe Zhang

Estimating the volume of a high-dimensional convex body is a fundamental problem in theoretical computer science. Given a quantum membership oracle for a convex body $K\subset\mathbb{R}^d$, we show that estimating $\mathrm{vol}(K)$ to relative error $\varepsilon$ takes $\widetilde O(d^{5/2}+d^{3/2}/\varepsilon)$ queries. This improves the previous quantum upper bound $\widetilde O(d^3+d^{9/4}/\varepsilon)$ of Chakrabarti et al. (ACM TQC 2023) and Cornelissen--Hamoudi (SODA 2023), and achieves a larger quantum speedup over the currently best classical upper bound $\widetilde O(d^{7/2}+d^3/\varepsilon^2)$ of Jia et al. (JACM 2026). Our quantum algorithm combines two new ingredients: an input-dependent effective spectral-gap analysis of quantum walks based on uniform classical warm-start mixing bounds, and a single quantum estimator for products of normalizer ratios in simulated annealing based on classical bridge sampling. We also prove an $Ω(d)$ quantum query lower bound for constant relative error, improving the previous $Ω(\sqrt d)$ lower bound.

Tuesday, October 06 2026, 00:00

Fair Diversity Maximization via Local Search

Authors: Mohammad Ansari, Sina Azizeddin, AmirMohammad Bandari, Pouria Mahmoudkhan, Hamid Zarabi-Zadeh

Diversity maximization is a fundamental optimization problem with applications in machine learning, data summarization, information retrieval, and recommendation systems. In many such applications, the data are partitioned into groups, and the selected subset must satisfy prescribed group quotas. We study Fair Diversity Maximization: given a set of points in a metric space partitioned into $m$ groups, the goal is to select exactly $k_i$ points from each group $i$ while maximizing the minimum pairwise distance among the selected points. The best previously known approximation guarantee is $m+1$, which grows linearly with the number of groups. We show that this dependence on $m$ is not fundamental. We present a new local-search framework that yields a $4$-approximation for any constant number of groups, with no restrictions on the metric space or on the size of the selected set. To the best of our knowledge, this is the first constant-factor approximation whose guarantee is independent of the number of groups in this general setting. Our framework maintains all group quotas exactly while progressively eliminating violations of the diversity objective. We further develop a specialized algorithm for two groups that achieves a $2$-approximation, improving the previous best factor of $3$. This factor is optimal: unless $\mathrm{P}=\mathrm{NP}$, no polynomial-time algorithm can achieve an approximation factor strictly better than $2$, even for the unconstrained case.

Authors: Mohammad Ansari, Sina Azizeddin, AmirMohammad Bandari, Pouria Mahmoudkhan, Hamid Zarabi-Zadeh

Diversity maximization is a fundamental optimization problem with applications in machine learning, data summarization, information retrieval, and recommendation systems. In many such applications, the data are partitioned into groups, and the selected subset must satisfy prescribed group quotas. We study Fair Diversity Maximization: given a set of points in a metric space partitioned into $m$ groups, the goal is to select exactly $k_i$ points from each group $i$ while maximizing the minimum pairwise distance among the selected points. The best previously known approximation guarantee is $m+1$, which grows linearly with the number of groups. We show that this dependence on $m$ is not fundamental. We present a new local-search framework that yields a $4$-approximation for any constant number of groups, with no restrictions on the metric space or on the size of the selected set. To the best of our knowledge, this is the first constant-factor approximation whose guarantee is independent of the number of groups in this general setting. Our framework maintains all group quotas exactly while progressively eliminating violations of the diversity objective. We further develop a specialized algorithm for two groups that achieves a $2$-approximation, improving the previous best factor of $3$. This factor is optimal: unless $\mathrm{P}=\mathrm{NP}$, no polynomial-time algorithm can achieve an approximation factor strictly better than $2$, even for the unconstrained case.

Tuesday, October 06 2026, 00:00

CV-QAOA: Efficient Low-Depth Quantum Optimization of Continuous Variables

Authors: Sriram Bharadwaj, Di Luo, Leo Zhou

We study a Continuous-Variable Quantum Approximate Optimization Algorithm (CV-QAOA) for high-dimensional continuous optimization. Our formulation extends an earlier CV-QAOA proposal with a variationally optimized initial state and recovers the convergence guarantees of Quantum Hamiltonian Descent (QHD) in the high-depth limit. We prove rigorous performance guarantees of CV-QAOA on several families of cost functions. First, we show $d$-step CV-QAOA minimizes any $d$-dimensional strictly convex quadratic function with $2d$ quantum queries to the cost function. We then analyze a family of nonconvex "Rotated Double Well" (RDW) functions with $2^d$ local minima introduced by arXiv:2311.00811. While prior work showed QHD reaches its global minimum with $\tilde O(d^3)$ queries, we prove that 1-step CV-QAOA solves RDW with just two quantum queries. Although general-purpose classical solvers need superpolynomial time for RDW and structure-awareness can reduce the cost to polynomial time, we show that the 1-step CV-QAOA protocol can be efficiently dequantized, and that a gradient-aligned line search succeeds with $O(d)$ queries, nearly matching the information-theoretic $Ω(d/\log d)$ query lower bound. To move beyond the dequantizable regime, we introduce a ``Rotated Square Well'' (RSW) problem, whose globally flat landscape suppresses useful local gradient information. For this family, we show that an adiabatic evolution simulated by CV-QAOA can reach the global minimum using $d^{o(1)}$ queries. On the other hand, any classical algorithm that learn the hidden rotation in RSW provably requires $Ω(d^2/\log d)$ queries, a bound we nearly match with an explicit $Θ(d^2\log d)$-query classical algorithm.Numerical simulations on deflected corrugated spring and Easom functions illustrate the promising performance of CV-QAOA on more general problems.

Authors: Sriram Bharadwaj, Di Luo, Leo Zhou

We study a Continuous-Variable Quantum Approximate Optimization Algorithm (CV-QAOA) for high-dimensional continuous optimization. Our formulation extends an earlier CV-QAOA proposal with a variationally optimized initial state and recovers the convergence guarantees of Quantum Hamiltonian Descent (QHD) in the high-depth limit. We prove rigorous performance guarantees of CV-QAOA on several families of cost functions. First, we show $d$-step CV-QAOA minimizes any $d$-dimensional strictly convex quadratic function with $2d$ quantum queries to the cost function. We then analyze a family of nonconvex "Rotated Double Well" (RDW) functions with $2^d$ local minima introduced by arXiv:2311.00811. While prior work showed QHD reaches its global minimum with $\tilde O(d^3)$ queries, we prove that 1-step CV-QAOA solves RDW with just two quantum queries. Although general-purpose classical solvers need superpolynomial time for RDW and structure-awareness can reduce the cost to polynomial time, we show that the 1-step CV-QAOA protocol can be efficiently dequantized, and that a gradient-aligned line search succeeds with $O(d)$ queries, nearly matching the information-theoretic $Ω(d/\log d)$ query lower bound. To move beyond the dequantizable regime, we introduce a ``Rotated Square Well'' (RSW) problem, whose globally flat landscape suppresses useful local gradient information. For this family, we show that an adiabatic evolution simulated by CV-QAOA can reach the global minimum using $d^{o(1)}$ queries. On the other hand, any classical algorithm that learn the hidden rotation in RSW provably requires $Ω(d^2/\log d)$ queries, a bound we nearly match with an explicit $Θ(d^2\log d)$-query classical algorithm.Numerical simulations on deflected corrugated spring and Easom functions illustrate the promising performance of CV-QAOA on more general problems.

Tuesday, October 06 2026, 00:00

Finding Gaussian Structure in Bosonic States

Authors: Alvan Arulandu, Sitan Chen, Ziyun Chen, Jerry Li, Eric Ma

We study agnostic tomography of pure bosonic Gaussian states: given copies of an arbitrary $n$-mode bosonic state $ρ$, the goal is to output a pure Gaussian state whose infidelity with $ρ$ is at most $\mathrm{opt} + ε$, where $\mathrm{opt}$ is the minimum infidelity achievable by any pure Gaussian state. We give efficient protocols achieving this in both the high and low fidelity regimes. When $\mathrm{opt}$ is below some universal constant, our protocol has runtime and copy complexity which is strongly polynomial in $n, 1/ε$ and $\log \log E$, where $E$ is the energy of the closest pure Gaussian state. For arbitrary $\mathrm{opt}$, our protocol uses $(n+1)^{\mathrm{poly}(1/ε)} \mathrm{poly}\left(1+\log\log(E)\right)$ copies and runtime. As a corollary, we obtain the first truly tolerant Gaussianity testing protocol for distinguishing whether $\mathrm{opt} > c + ε$ or $\mathrm{opt} < c - ε$, for any threshold $c\in(0,1)$. We also prove $\mathrm{poly}(n,1/ε)$ runtime is impossible, unless $\mathrm{NP}\subseteq\mathrm{BQP}$. Our protocols follow a shared paradigm: first, we iteratively use general Gaussian measurements combined with techniques from classical robust statistics to obtain a good warm start estimate, then we leverage non-Gaussian measurements to refine this warm start using convex and non-convex optimization methods. Interestingly, we prove that non-Gaussian measurements are necessary to match the strong agnostic guarantees we obtain, and in fact these guarantees are provably superior to what is possible for robustly estimating classical Gaussians.

Authors: Alvan Arulandu, Sitan Chen, Ziyun Chen, Jerry Li, Eric Ma

We study agnostic tomography of pure bosonic Gaussian states: given copies of an arbitrary $n$-mode bosonic state $ρ$, the goal is to output a pure Gaussian state whose infidelity with $ρ$ is at most $\mathrm{opt} + ε$, where $\mathrm{opt}$ is the minimum infidelity achievable by any pure Gaussian state. We give efficient protocols achieving this in both the high and low fidelity regimes. When $\mathrm{opt}$ is below some universal constant, our protocol has runtime and copy complexity which is strongly polynomial in $n, 1/ε$ and $\log \log E$, where $E$ is the energy of the closest pure Gaussian state. For arbitrary $\mathrm{opt}$, our protocol uses $(n+1)^{\mathrm{poly}(1/ε)} \mathrm{poly}\left(1+\log\log(E)\right)$ copies and runtime. As a corollary, we obtain the first truly tolerant Gaussianity testing protocol for distinguishing whether $\mathrm{opt} > c + ε$ or $\mathrm{opt} < c - ε$, for any threshold $c\in(0,1)$. We also prove $\mathrm{poly}(n,1/ε)$ runtime is impossible, unless $\mathrm{NP}\subseteq\mathrm{BQP}$. Our protocols follow a shared paradigm: first, we iteratively use general Gaussian measurements combined with techniques from classical robust statistics to obtain a good warm start estimate, then we leverage non-Gaussian measurements to refine this warm start using convex and non-convex optimization methods. Interestingly, we prove that non-Gaussian measurements are necessary to match the strong agnostic guarantees we obtain, and in fact these guarantees are provably superior to what is possible for robustly estimating classical Gaussians.

Tuesday, October 06 2026, 00:00

Quantum 1-PCA with Pauli Measurements in Nearly Linear Time

Authors: Dutch Hansen, Jerry Li

We consider the problem of quantum 1-PCA: given copies of an unknown $n$-qubit mixed state, recover a classical description of its leading eigenvector. Our goal is to do so using non-adaptive and single-qubit measurements. For an $n$-qubit state with top eigenvalue $λ$ and spectral gap at least $Δ> 0$, we give an algorithm that recovers the leading eigenvector to fidelity at least $1 - \varepsilon$ with high probability using $\tilde{O}\left( {2^n \cdot η^2} / {Δ^3 \varepsilon^3}\right)$ copies and $\tilde{O}((2^n/Δ\varepsilon) \cdot \operatorname{poly}(η/Δ\varepsilon))$ time, where $η= \max (1 - λ, \varepsilon)$. All of our measurements are non-adaptively chosen, and performed in single-qubit Pauli bases. When the spectral gap is constant and the desired accuracy is comparable to the noise level, i.e. $\varepsilon = Ω(η)$, our runtime and copy complexity become $\tilde{O} (2^n / \varepsilon)$. This generalizes the guarantees of Grewal et al. [arXiv:2601.04444], who achieved similar rates, but under the assumption $η= 0$, i.e., that the state was pure. Our results show that the same rates hold in the presence of state misspecification, up to polylogarithmic factors. From a technical perspective, our algorithm works by recursively constructing low-dimensional subspaces that approximately preserve the target eigenvector. To achieve nearly linear runtime dependence on the dimension of the Hilbert space, we develop a novel structured Pauli sampling scheme that enables fast batched computation of exponentially many projected Pauli matrices.

Authors: Dutch Hansen, Jerry Li

We consider the problem of quantum 1-PCA: given copies of an unknown $n$-qubit mixed state, recover a classical description of its leading eigenvector. Our goal is to do so using non-adaptive and single-qubit measurements. For an $n$-qubit state with top eigenvalue $λ$ and spectral gap at least $Δ> 0$, we give an algorithm that recovers the leading eigenvector to fidelity at least $1 - \varepsilon$ with high probability using $\tilde{O}\left( {2^n \cdot η^2} / {Δ^3 \varepsilon^3}\right)$ copies and $\tilde{O}((2^n/Δ\varepsilon) \cdot \operatorname{poly}(η/Δ\varepsilon))$ time, where $η= \max (1 - λ, \varepsilon)$. All of our measurements are non-adaptively chosen, and performed in single-qubit Pauli bases. When the spectral gap is constant and the desired accuracy is comparable to the noise level, i.e. $\varepsilon = Ω(η)$, our runtime and copy complexity become $\tilde{O} (2^n / \varepsilon)$. This generalizes the guarantees of Grewal et al. [arXiv:2601.04444], who achieved similar rates, but under the assumption $η= 0$, i.e., that the state was pure. Our results show that the same rates hold in the presence of state misspecification, up to polylogarithmic factors. From a technical perspective, our algorithm works by recursively constructing low-dimensional subspaces that approximately preserve the target eigenvector. To achieve nearly linear runtime dependence on the dimension of the Hilbert space, we develop a novel structured Pauli sampling scheme that enables fast batched computation of exponentially many projected Pauli matrices.

Tuesday, October 06 2026, 00:00

Polynomial-time classical algorithms for mean-field models up to the glass transition

Authors: Alexander Schmidhuber, Alexander Zlokapa

The Sachdev-Ye-Kitaev model is a strongly interacting fermionic system that has been well-studied in condensed matter and high energy physics. It is highly quantum: Gaussian states are far from the thermal state (Hastings and O'Donnell, STOC'22) and representing the thermal state requires large polynomial-size quantum circuits (Anschuetz et al., QIP'25). Very recently, it was nonetheless proven that classical algorithms can estimate local thermal expectations at sufficiently high temperature in quasipolynomial time (Zlokapa, FOCS'26). We show that classical algorithms can in fact estimate local observables at all constant temperatures in polynomial time. Our techniques also extend straightforwardly to classical systems: we resolve an open question about computing thermal expectations of a classical spin glass up to its phase transition (Bencs et al., STOC'26). Our proof develops a fully rigorous quantum cavity method. Due to the success of the classical cavity method in optimization, sampling, inference and learning, we expect the quantum cavity method to find further applications of independent interest. As an example, we give a quantum algorithm that learns SYK Hamiltonians from the Gibbs state at any constant temperature with polynomial time and sample complexity.

Authors: Alexander Schmidhuber, Alexander Zlokapa

The Sachdev-Ye-Kitaev model is a strongly interacting fermionic system that has been well-studied in condensed matter and high energy physics. It is highly quantum: Gaussian states are far from the thermal state (Hastings and O'Donnell, STOC'22) and representing the thermal state requires large polynomial-size quantum circuits (Anschuetz et al., QIP'25). Very recently, it was nonetheless proven that classical algorithms can estimate local thermal expectations at sufficiently high temperature in quasipolynomial time (Zlokapa, FOCS'26). We show that classical algorithms can in fact estimate local observables at all constant temperatures in polynomial time. Our techniques also extend straightforwardly to classical systems: we resolve an open question about computing thermal expectations of a classical spin glass up to its phase transition (Bencs et al., STOC'26). Our proof develops a fully rigorous quantum cavity method. Due to the success of the classical cavity method in optimization, sampling, inference and learning, we expect the quantum cavity method to find further applications of independent interest. As an example, we give a quantum algorithm that learns SYK Hamiltonians from the Gibbs state at any constant temperature with polynomial time and sample complexity.

Tuesday, October 06 2026, 00:00

Approximating Random Walks in $\widetilde{O}(\log n + \log^2 κ)$ Space for $κ$-Conditioned Graphs

Authors: Junzhao Yang

For $κ>1$, a directed graph is $κ$-conditioned if it is $κ$-mixing and its stationary distribution is approximated by the uniform distribution within a factor of $κ$. We present a deterministic algorithm that approximates the stationary distribution of a $κ$-conditioned graph to inverse polynomial relative error in $O((\log n + \log^2 κ) \log \log n)$ space. In the regime $κ= \exp(Θ(\log^αn))$ for any $α\in (0, 2/3)$, our result improves the best-known $O(\log n \sqrt{\log κ} / \sqrt{\log \log n})$ space bound for approximating $κ$-step random walks in general directed graphs by [Hoza, RANDOM 2021]. We release this preliminary version due to recent rumors of LLM-based progress on related problems and uncertainty about when those results may appear. Further implementation details will be provided in a subsequent version.

Authors: Junzhao Yang

For $κ>1$, a directed graph is $κ$-conditioned if it is $κ$-mixing and its stationary distribution is approximated by the uniform distribution within a factor of $κ$. We present a deterministic algorithm that approximates the stationary distribution of a $κ$-conditioned graph to inverse polynomial relative error in $O((\log n + \log^2 κ) \log \log n)$ space. In the regime $κ= \exp(Θ(\log^αn))$ for any $α\in (0, 2/3)$, our result improves the best-known $O(\log n \sqrt{\log κ} / \sqrt{\log \log n})$ space bound for approximating $κ$-step random walks in general directed graphs by [Hoza, RANDOM 2021]. We release this preliminary version due to recent rumors of LLM-based progress on related problems and uncertainty about when those results may appear. Further implementation details will be provided in a subsequent version.

Tuesday, October 06 2026, 00:00

Random Order in Quantum Streaming: Replenishment and Robust Lower Bounds

Authors: Nadezhda Voronova

How can random order change the role of quantum memory in streaming? Later classical input can restore the usefulness of a quantum state consumed by earlier queries. We call this replenishment. We construct an artificial problem based on Hidden Matching, with repeated coordinate data and online matching requests. It admits a one-pass quantum algorithm using polylogarithmic space in uniformly random order, but unconditionally requires polynomial space both classically in random order and quantumly when all updates precede the requests. To prove the quantum lower bound, we strengthen the consumability bounds of Gilboa, Jain, and McClean for Multiple Hidden Matching. Without prior entanglement, any quantum encoding supporting $r$ independent matching requests requires $Ω(r)$ qubits for $r\le N^{1/2-δ}$ and every fixed $δ\in(0,1/2)$, even with simultaneous revelation and arbitrary joint decoding. For sequential requests, the linear bound extends through $r=Θ(\sqrt N)$. We also adapt Kallaugher's triangle-counting algorithm to uniformly random streams in which every edge is repeated equally often. Rebuilding the quantum sketch and resampling the classical estimator improve its expected-space bound in suitable parameter regimes. Finally, we extend the robust Noisy Gap Cycle framework of Assadi and Sundaresan to quantum streaming. A quantum communication lower bound for Block Hidden XOR yields an $Ω(n)$ space lower bound in random edge order for large enough cycles, with consequences for several graph problems. Thus random order can enable replenishment of small quantum representations, while substantial space requirements persist for other tasks.

Authors: Nadezhda Voronova

How can random order change the role of quantum memory in streaming? Later classical input can restore the usefulness of a quantum state consumed by earlier queries. We call this replenishment. We construct an artificial problem based on Hidden Matching, with repeated coordinate data and online matching requests. It admits a one-pass quantum algorithm using polylogarithmic space in uniformly random order, but unconditionally requires polynomial space both classically in random order and quantumly when all updates precede the requests. To prove the quantum lower bound, we strengthen the consumability bounds of Gilboa, Jain, and McClean for Multiple Hidden Matching. Without prior entanglement, any quantum encoding supporting $r$ independent matching requests requires $Ω(r)$ qubits for $r\le N^{1/2-δ}$ and every fixed $δ\in(0,1/2)$, even with simultaneous revelation and arbitrary joint decoding. For sequential requests, the linear bound extends through $r=Θ(\sqrt N)$. We also adapt Kallaugher's triangle-counting algorithm to uniformly random streams in which every edge is repeated equally often. Rebuilding the quantum sketch and resampling the classical estimator improve its expected-space bound in suitable parameter regimes. Finally, we extend the robust Noisy Gap Cycle framework of Assadi and Sundaresan to quantum streaming. A quantum communication lower bound for Block Hidden XOR yields an $Ω(n)$ space lower bound in random edge order for large enough cycles, with consequences for several graph problems. Thus random order can enable replenishment of small quantum representations, while substantial space requirements persist for other tasks.

Tuesday, October 06 2026, 00:00

Near-Optimal Oracle Bounds for Isotropic Rounding

Authors: Yang P. Liu, Richard Peng, Alicia Stepin, Colin Tang

We give optimal bounds, up to polylogarithmic factors, for rounding convex bodies to near-isotropic position. A convex body $B(0,r)\subseteq K\subseteq B(0,R)$ in $\R^n$ can be rounded using $\Ot(n^3)$ membership queries; the upper bound extends to logconcave distributions. We prove a matching $\Omegat(n^3)$ lower bound, even when $R/r=n^{O(1)}$. The key lemma states that if $B(0,1)\subseteq K$ and $\Cov(\Unif(K))\preceqκI_n$, with $κ\ge1$, then approximate uniform sampling from an initial density bounded by a constant times the uniform density uses $\Ot(n^2\sqrtκ)$ expected membership queries. We prove this by simulating reflected kinetic dynamics using the analysis of Eberle and Lörler~\cite{EL26:journal}. Combining this sampler with the ideas of Jia, Laddha, Lee, and Vempala~\cite{JLLV26:journal} for rounding well-rounded bodies yields our $\Ot(n^3)$ query rounding algorithm. We also give a counterexample to an ellipsoid-growth conjecture from previous papers on this topic.

Authors: Yang P. Liu, Richard Peng, Alicia Stepin, Colin Tang

We give optimal bounds, up to polylogarithmic factors, for rounding convex bodies to near-isotropic position. A convex body $B(0,r)\subseteq K\subseteq B(0,R)$ in $\R^n$ can be rounded using $\Ot(n^3)$ membership queries; the upper bound extends to logconcave distributions. We prove a matching $\Omegat(n^3)$ lower bound, even when $R/r=n^{O(1)}$. The key lemma states that if $B(0,1)\subseteq K$ and $\Cov(\Unif(K))\preceqκI_n$, with $κ\ge1$, then approximate uniform sampling from an initial density bounded by a constant times the uniform density uses $\Ot(n^2\sqrtκ)$ expected membership queries. We prove this by simulating reflected kinetic dynamics using the analysis of Eberle and Lörler~\cite{EL26:journal}. Combining this sampler with the ideas of Jia, Laddha, Lee, and Vempala~\cite{JLLV26:journal} for rounding well-rounded bodies yields our $\Ot(n^3)$ query rounding algorithm. We also give a counterexample to an ellipsoid-growth conjecture from previous papers on this topic.

Tuesday, October 06 2026, 00:00

Optimal compression with quantum retrieval

Authors: Shyam Dhamapurkar, Mohit Garg, Manaswi Paraashar, Jaikumar Radhakrishnan

We consider the following data compression problem. Given a string $x \in \{0,1\}^m$ of Hamming weight at most $n$, compress it into a shorter string $y \in \{0,1\}^s$ so that any bit $x_i$ of $x$ can be retrieved without any error using at most $t$ quantum queries to the standard oracle encoding of $y$. If queries are allowed to be adaptive we show how optimal compression up to a logarithmic factor can be achieved. If the queries are required to be made non-adaptively, we show schemes whose space is optimal in its dependence on $m$ except for a logarithmic factor, and is at most quadratically worse when compared to the optimum in its dependence on $n$.

Authors: Shyam Dhamapurkar, Mohit Garg, Manaswi Paraashar, Jaikumar Radhakrishnan

We consider the following data compression problem. Given a string $x \in \{0,1\}^m$ of Hamming weight at most $n$, compress it into a shorter string $y \in \{0,1\}^s$ so that any bit $x_i$ of $x$ can be retrieved without any error using at most $t$ quantum queries to the standard oracle encoding of $y$. If queries are allowed to be adaptive we show how optimal compression up to a logarithmic factor can be achieved. If the queries are required to be made non-adaptively, we show schemes whose space is optimal in its dependence on $m$ except for a logarithmic factor, and is at most quadratically worse when compared to the optimum in its dependence on $n$.

Tuesday, October 06 2026, 00:00

Faster high-accuracy multicommodity flow in dense graphs

Authors: Chenxin Dai, Alicia Stepin, Colin Tang

We give a fast algorithm for solving min-cost $k$-commodity flow. The basic idea is to construct an auxiliary linear program that has low rank and whose minimum value is at most $1/k$ times the minimum value of the original problem (thus, solving this auxiliary linear program will make at least $1/k$ fraction of progress in the original problem). Low-rank linear programs can be solved quickly using black-box techniques. Thus, our algorithm runs in time $\tilde{O}(\operatorname{poly}(k)(n^{2.5}+m\sqrt{n}))$ on a directed graph with $n$ vertices and $m$ edges. We do not rely on any fast matrix multiplication.

Authors: Chenxin Dai, Alicia Stepin, Colin Tang

We give a fast algorithm for solving min-cost $k$-commodity flow. The basic idea is to construct an auxiliary linear program that has low rank and whose minimum value is at most $1/k$ times the minimum value of the original problem (thus, solving this auxiliary linear program will make at least $1/k$ fraction of progress in the original problem). Low-rank linear programs can be solved quickly using black-box techniques. Thus, our algorithm runs in time $\tilde{O}(\operatorname{poly}(k)(n^{2.5}+m\sqrt{n}))$ on a directed graph with $n$ vertices and $m$ edges. We do not rely on any fast matrix multiplication.

Tuesday, October 06 2026, 00:00

A Decremental Algorithm for Checking the Possibility of Braess Paradox in Dynamic Nets

Authors: Dario Fiorenza, Daniele Gorla, Ivano Salvo

Braess paradox originates when latency at Wardrop equilibrium in traffic networks decreases because of removing edges. The graph-theoretic property of networks suffering from the Braess paradox was called vulnerability by Roughgarden in 2006; it was then characterized and algorithmically checked both for undirected and for directed nets. In this paper, we provide a decremental algorithm of linear amortized complexity to check vulnerability for dynamically evolving networks. The basic idea of our dynamic algorithm is to use a static algorithm that marks some edges as irrelevant for the vulnerability of the graph and ignore those edges for all subsequent runs of the decremental procedure. To get a linear amortized cost for every edge remotion, we also provide a new version of such a static algorithm that improves its complexity from O(n m^2) to O(m^2), that is in turn aligned with the cost of the best state-of-the-art static algorithm for vulnerability.

Authors: Dario Fiorenza, Daniele Gorla, Ivano Salvo

Braess paradox originates when latency at Wardrop equilibrium in traffic networks decreases because of removing edges. The graph-theoretic property of networks suffering from the Braess paradox was called vulnerability by Roughgarden in 2006; it was then characterized and algorithmically checked both for undirected and for directed nets. In this paper, we provide a decremental algorithm of linear amortized complexity to check vulnerability for dynamically evolving networks. The basic idea of our dynamic algorithm is to use a static algorithm that marks some edges as irrelevant for the vulnerability of the graph and ignore those edges for all subsequent runs of the decremental procedure. To get a linear amortized cost for every edge remotion, we also provide a new version of such a static algorithm that improves its complexity from O(n m^2) to O(m^2), that is in turn aligned with the cost of the best state-of-the-art static algorithm for vulnerability.

Tuesday, October 06 2026, 00:00

Sharp dimensional analysis of midpoint methods for Langevin sampling

Authors: Fan Chen, Sinho Chewi, Jianfeng Lu, Matthew S. Zhang

We study deterministic and randomized midpoint discretizations of Langevin dynamics for a target $π\propto e^{-V}$, where $0 \prec αI\preceq\nabla^2V\preceqβI$ and $κ=β/α$. To achieve $\sqrtα\,W_2\leqslant\varepsilon$, we show that deterministic Heun uses at most $\widetilde O(κ^{4/3}d^{1/3}\varepsilon^{-2/3})$ gradient queries, and underdamped exponential midpoint uses $\widetilde O(κ^{5/4}d^{1/4}\varepsilon^{-1/2})$. The proofs exploit cancellation at stationarity and smoothing using techniques from Malliavin calculus, outperforming previous upper bounds based on standard couplings. At bounded condition number, a lower bound matches the $d$ and $\varepsilon$ powers of both deterministic methods. To contrast, for the randomized midpoint methods and Poisson midpoint with at least two grid points (both overdamped and underdamped variants), a simple Gaussian calculation yields a lower bound $d^{1/3}\varepsilon^{-1/3}$ to get an $\varepsilon$-close sample despite starting at a benign initialization. This shows surprisingly that in high dimensions, deterministic discretizations can outperform their random counterparts.

Authors: Fan Chen, Sinho Chewi, Jianfeng Lu, Matthew S. Zhang

We study deterministic and randomized midpoint discretizations of Langevin dynamics for a target $π\propto e^{-V}$, where $0 \prec αI\preceq\nabla^2V\preceqβI$ and $κ=β/α$. To achieve $\sqrtα\,W_2\leqslant\varepsilon$, we show that deterministic Heun uses at most $\widetilde O(κ^{4/3}d^{1/3}\varepsilon^{-2/3})$ gradient queries, and underdamped exponential midpoint uses $\widetilde O(κ^{5/4}d^{1/4}\varepsilon^{-1/2})$. The proofs exploit cancellation at stationarity and smoothing using techniques from Malliavin calculus, outperforming previous upper bounds based on standard couplings. At bounded condition number, a lower bound matches the $d$ and $\varepsilon$ powers of both deterministic methods. To contrast, for the randomized midpoint methods and Poisson midpoint with at least two grid points (both overdamped and underdamped variants), a simple Gaussian calculation yields a lower bound $d^{1/3}\varepsilon^{-1/3}$ to get an $\varepsilon$-close sample despite starting at a benign initialization. This shows surprisingly that in high dimensions, deterministic discretizations can outperform their random counterparts.

Tuesday, October 06 2026, 00:00

Hiding a Vertex from the Temporal Explorer: A Lower Bound for Degree-Bounded Temporal Graphs

Authors: Daniele Carnevale

A temporal graph is a sequence of graphs on a common set of $n$ vertices, its snapshots, one for each time step. An agent, knowing the entire sequence in advance, may at each time step wait or move along an edge of the current snapshot, and the temporal graph is explored once the agent has visited every vertex. We consider always-connected temporal graphs, in which every snapshot is connected, and ask how long exploration can be forced to take when the underlying graph, the union of all snapshots, has maximum degree at most~$Δ$. Two lower bounds were known in this setting, $Ω(Δn)$ and $Ω(n\log n)$, realised by different constructions. We establish a stronger lower bound, answering a question of Bastide, Groenland, Michel and Rambaud. Specifically, for every $n$ and $Δ$ with $Δ_0\leΔ\le n-1$ we construct an always-connected temporal graph on $n$ vertices with underlying maximum degree at most~$Δ$ that cannot be explored in fewer than $γ\,Δn\,(1+\log(n/Δ))$ time steps from any start vertex, where $γ>0$ and $Δ_0$ are absolute constants. The construction is deterministic, and every snapshot is a spanning tree with exactly one vertex of degree greater than three. Time is divided into phases. In each phase, a rotating-cycle gadget prevents the agent from reaching more than half of the trees attached to it. Between phases, we reassign target vertices among these trees using walks on a constant-degree expander, and a Gray code order of the targets keeps the underlying degree bounded. The reassignment guarantees that, for any walk of the agent, some target remains unvisited throughout all phases.

Authors: Daniele Carnevale

A temporal graph is a sequence of graphs on a common set of $n$ vertices, its snapshots, one for each time step. An agent, knowing the entire sequence in advance, may at each time step wait or move along an edge of the current snapshot, and the temporal graph is explored once the agent has visited every vertex. We consider always-connected temporal graphs, in which every snapshot is connected, and ask how long exploration can be forced to take when the underlying graph, the union of all snapshots, has maximum degree at most~$Δ$. Two lower bounds were known in this setting, $Ω(Δn)$ and $Ω(n\log n)$, realised by different constructions. We establish a stronger lower bound, answering a question of Bastide, Groenland, Michel and Rambaud. Specifically, for every $n$ and $Δ$ with $Δ_0\leΔ\le n-1$ we construct an always-connected temporal graph on $n$ vertices with underlying maximum degree at most~$Δ$ that cannot be explored in fewer than $γ\,Δn\,(1+\log(n/Δ))$ time steps from any start vertex, where $γ>0$ and $Δ_0$ are absolute constants. The construction is deterministic, and every snapshot is a spanning tree with exactly one vertex of degree greater than three. Time is divided into phases. In each phase, a rotating-cycle gadget prevents the agent from reaching more than half of the trees attached to it. Between phases, we reassign target vertices among these trees using walks on a constant-degree expander, and a Gray code order of the targets keeps the underlying degree bounded. The reassignment guarantees that, for any walk of the agent, some target remains unvisited throughout all phases.

Tuesday, October 06 2026, 00:00

On the Parameterized Complexity of Conflict-Free Edge Cut in Undirected Graphs

Authors: Sourav Das, Ashwin Jacob, Arpit Kumar, Diptapriyo Majumdar

In this paper, we study CONFLICT-FREE EDGE CUT (CF-CUT), which is a recently introduced conflict-free version of the MIN-CUT problem that asks to find the minimum number of edges to disconnect a connected graph. The CF-CUT takes as input a connected undirected graph G = (V, E), a conflict graph $\widehat{G}$ such that $E(G) = V(\widehat{G})$, and the objective is to decide whether there exists $F \subseteq E(G)$ such that $G - F$ is disconnected and $F$ is an independent set in $\widehat{G}$. Rauch et. al. [IPL-2025] proved that CF-CUT is NP-Complete and also provided some results on the parameterized complexity of CF-CUT. A related variant MIN CONFLICT-FREE EDGE CUT (MIN-CF-CUT) takes a connected graph $G$, a conflict graph $\widehat{G}$ such that $V(\widehat{G}) = E(G)$, and an integer $k$ as input and asks if there is a set $F$ of at most $k$ edges such that $G - F$ is disconnected and $F$ is an independent set in $\widehat{G}$. In this paper, we extend the work of Rauch et al. [IPL-2025] and provide a systematic study on the CF-CUT and MIN-CF-CUT from the perspective of parameterized complexity and polynomial kernelization. We prove that CF-CUT is NP-hard when the dissociation number of the input graph is at most two. We also complement it by proving that CF-CUT is poly-time solvable when the dissociation number of an input graph is at most one. Additionally, for MIN-CF-CUT, we consider both solution size and various structural parameters of the input graph as parameters, and provide fixed-parameter tractability and W[1]-hardness results when the conflict graph is restricted to various graph classes. We also prove that unless NP $\subseteq$ coNP/poly, MIN-CF-CUT admits no polynomial kernel when parameterized by the vertex cover number of the input graph; and also when parameterized by the sum of the solution size and the vertex integrity of the input graph.

Authors: Sourav Das, Ashwin Jacob, Arpit Kumar, Diptapriyo Majumdar

In this paper, we study CONFLICT-FREE EDGE CUT (CF-CUT), which is a recently introduced conflict-free version of the MIN-CUT problem that asks to find the minimum number of edges to disconnect a connected graph. The CF-CUT takes as input a connected undirected graph G = (V, E), a conflict graph $\widehat{G}$ such that $E(G) = V(\widehat{G})$, and the objective is to decide whether there exists $F \subseteq E(G)$ such that $G - F$ is disconnected and $F$ is an independent set in $\widehat{G}$. Rauch et. al. [IPL-2025] proved that CF-CUT is NP-Complete and also provided some results on the parameterized complexity of CF-CUT. A related variant MIN CONFLICT-FREE EDGE CUT (MIN-CF-CUT) takes a connected graph $G$, a conflict graph $\widehat{G}$ such that $V(\widehat{G}) = E(G)$, and an integer $k$ as input and asks if there is a set $F$ of at most $k$ edges such that $G - F$ is disconnected and $F$ is an independent set in $\widehat{G}$. In this paper, we extend the work of Rauch et al. [IPL-2025] and provide a systematic study on the CF-CUT and MIN-CF-CUT from the perspective of parameterized complexity and polynomial kernelization. We prove that CF-CUT is NP-hard when the dissociation number of the input graph is at most two. We also complement it by proving that CF-CUT is poly-time solvable when the dissociation number of an input graph is at most one. Additionally, for MIN-CF-CUT, we consider both solution size and various structural parameters of the input graph as parameters, and provide fixed-parameter tractability and W[1]-hardness results when the conflict graph is restricted to various graph classes. We also prove that unless NP $\subseteq$ coNP/poly, MIN-CF-CUT admits no polynomial kernel when parameterized by the vertex cover number of the input graph; and also when parameterized by the sum of the solution size and the vertex integrity of the input graph.

Tuesday, October 06 2026, 00:00

Improved Sublinear Algorithms for Maximal Independent Set and Metric Steiner Forest

Authors: Sepideh Mahabadi, Jakub Tarnawski

In this work we consider the Maximal Independent Set (MIS) problem and the metric Steiner Forest problem in the sublinear time setting, under the adjacency/distance matrix query model. First, we give an algorithm that estimates the size of an MIS up to a multiplicative factor of $(1+\eps)$ using $\tO(n^{4/3}/\eps^2)$ queries. This improves the best previous algorithm by Mahabadi, Roghani, Tarnawski, and Vakilian (SODA 2026), which had a query complexity of $\tO(n^{3/2}/\eps^2)$. Via a reduction from that work, this would automatically imply the same improvement for the problem of estimating the metric Steiner Forest cost up to an $O(\log n)$ factor. However, as our second contribution, we consider the Steiner Forest problem directly and provide an algorithm with $\tO(n)$ query complexity that is very simple and does not proceed via MIS.

Authors: Sepideh Mahabadi, Jakub Tarnawski

In this work we consider the Maximal Independent Set (MIS) problem and the metric Steiner Forest problem in the sublinear time setting, under the adjacency/distance matrix query model. First, we give an algorithm that estimates the size of an MIS up to a multiplicative factor of $(1+\eps)$ using $\tO(n^{4/3}/\eps^2)$ queries. This improves the best previous algorithm by Mahabadi, Roghani, Tarnawski, and Vakilian (SODA 2026), which had a query complexity of $\tO(n^{3/2}/\eps^2)$. Via a reduction from that work, this would automatically imply the same improvement for the problem of estimating the metric Steiner Forest cost up to an $O(\log n)$ factor. However, as our second contribution, we consider the Steiner Forest problem directly and provide an algorithm with $\tO(n)$ query complexity that is very simple and does not proceed via MIS.

Tuesday, October 06 2026, 00:00

Near-Exact Computation of Independent Chip Model Placement Probabilities for Thousands of Players

Authors: Wataru Inariba

The Independent Chip Model (ICM) converts the chip stacks of the players remaining in a poker tournament into finishing-place probabilities and prize equities. It is the standard model in tournament solvers, but its definition considers all possible finishing orders, and exact computation has been regarded as intractable for large fields. The same mathematics appears in other fields; for instance, the ICM is a Plackett-Luce ranking model with stacks as weights. We present DE-ICM, a deterministic algorithm that computes the placement probabilities of all $n$ players for all paid places in $O(M n^{2})$ time, where the number $M$ of quadrature nodes is fixed for the admissible inputs and the target accuracy. Its numerical scheme allows the target to be set close to the accuracy of double-precision arithmetic. The algorithm evaluates a classical integral representation in which, conditional on a player's exponential clock, the number of players ahead is Poisson-binomial. A double-exponential quadrature on a single grid evaluates every integral; its truncation errors have closed-form bounds, and the step size, which controls the discretization error, follows from the field size. A numerically stable deconvolution then recovers each player's leave-one-out coefficients in $O(n)$ time from one shared product. On exactly solvable instances with up to 4,000 players, the worst observed relative error of an equity is $4.0 \times 10^{-14}$ and the worst absolute error of a placement probability $1.1 \times 10^{-14}$. The full placement matrix for 1,000 players takes 0.2 seconds on one CPU core.

Authors: Wataru Inariba

The Independent Chip Model (ICM) converts the chip stacks of the players remaining in a poker tournament into finishing-place probabilities and prize equities. It is the standard model in tournament solvers, but its definition considers all possible finishing orders, and exact computation has been regarded as intractable for large fields. The same mathematics appears in other fields; for instance, the ICM is a Plackett-Luce ranking model with stacks as weights. We present DE-ICM, a deterministic algorithm that computes the placement probabilities of all $n$ players for all paid places in $O(M n^{2})$ time, where the number $M$ of quadrature nodes is fixed for the admissible inputs and the target accuracy. Its numerical scheme allows the target to be set close to the accuracy of double-precision arithmetic. The algorithm evaluates a classical integral representation in which, conditional on a player's exponential clock, the number of players ahead is Poisson-binomial. A double-exponential quadrature on a single grid evaluates every integral; its truncation errors have closed-form bounds, and the step size, which controls the discretization error, follows from the field size. A numerically stable deconvolution then recovers each player's leave-one-out coefficients in $O(n)$ time from one shared product. On exactly solvable instances with up to 4,000 players, the worst observed relative error of an equity is $4.0 \times 10^{-14}$ and the worst absolute error of a placement probability $1.1 \times 10^{-14}$. The full placement matrix for 1,000 players takes 0.2 seconds on one CPU core.

Tuesday, October 06 2026, 00:00

Fast mixing of the SYK model at high temperatures

Authors: Yiyi Cai, Yongtao Zhan, Alexander Zlokapa

The Sachdev-Ye-Kitaev (SYK) model is a strongly interacting fermionic system. Its dynamics are difficult to analyze with Lieb-Robinson bounds and cluster expansions due to its all-to-all disordered interactions. We prove that, with high probability over the disorder, the SYK model admits a quantum Gibbs sampler with a system-size-independent spectral gap at sufficiently high constant temperatures. This yields polynomial-time preparation of SYK Gibbs states on a quantum computer. While prior non-rigorous computations that suggested SYK thermalization were limited to studying local correlators, we emphasize that our result holds up to arbitrary inverse polynomial trace distance. Our proof introduces the pseudo-Lindbladian approach to fermions and uses an especially simple SYK analysis based on a comparison to classical dynamics.

Authors: Yiyi Cai, Yongtao Zhan, Alexander Zlokapa

The Sachdev-Ye-Kitaev (SYK) model is a strongly interacting fermionic system. Its dynamics are difficult to analyze with Lieb-Robinson bounds and cluster expansions due to its all-to-all disordered interactions. We prove that, with high probability over the disorder, the SYK model admits a quantum Gibbs sampler with a system-size-independent spectral gap at sufficiently high constant temperatures. This yields polynomial-time preparation of SYK Gibbs states on a quantum computer. While prior non-rigorous computations that suggested SYK thermalization were limited to studying local correlators, we emphasize that our result holds up to arbitrary inverse polynomial trace distance. Our proof introduces the pseudo-Lindbladian approach to fermions and uses an especially simple SYK analysis based on a comparison to classical dynamics.

Tuesday, October 06 2026, 00:00

Prime factorisation of stable-matching instances: uniqueness, simultaneous products, and an exact census

Authors: Yoshiteru Ishida

Every balanced instance of the stable marriage problem with strict complete preferences has a unique finest partition into prime blocks, and that single partition simultaneously factors three different structures: the reachable execution digraph as a Cartesian product, the proposal-prefix antimatroid as a direct sum, and the stable-matching lattice as a direct product. The converse fails, and fails at every size from two on: two explicit families share the identical Boolean-cube execution while one is maximally decomposable with a single stable matching and the other is prime with n. Uniqueness yields an exact census, a recursion counting the prime instances at every size, under which exactly 88,478,208 of the 110,075,314,176 profiles with four agents on each side are decomposable and the decomposable fraction is asymptotically n! / n^(2n). The blocks are characterised as the square components of the mutual-rank filtration, so the partition is computable in polynomial time and the factorisation is a tool rather than only a fact.

Authors: Yoshiteru Ishida

Every balanced instance of the stable marriage problem with strict complete preferences has a unique finest partition into prime blocks, and that single partition simultaneously factors three different structures: the reachable execution digraph as a Cartesian product, the proposal-prefix antimatroid as a direct sum, and the stable-matching lattice as a direct product. The converse fails, and fails at every size from two on: two explicit families share the identical Boolean-cube execution while one is maximally decomposable with a single stable matching and the other is prime with n. Uniqueness yields an exact census, a recursion counting the prime instances at every size, under which exactly 88,478,208 of the 110,075,314,176 profiles with four agents on each side are decomposable and the decomposable fraction is asymptotically n! / n^(2n). The blocks are characterised as the square components of the mutual-rank filtration, so the partition is computable in polynomial time and the factorisation is a tool rather than only a fact.

Tuesday, October 06 2026, 00:00

The Infectious Vaccination Problem: a variant of Firefighting with Spreading Defence

Authors: Jessica Enright, Melissa A. Huggan, Ethan Hunter-Frankland, Margaret-Ellen Messinger, Dylan Pearson

The Firefighter Problem models a spreading process (originally a fire, alternatively an infection or rumour, for example) on a graph. A defender saves a single vertex per turn; after each defence, the fire spreads to the unburned and undefended neighbours of all burning vertices. Deciding whether a strategy exists for the defender to protect some targeted number of vertices is computationally hard in graphs in general, but tractable in some restricted cases. Inspired by research into spreadable rabies vaccines for bats, we study a variant of the Firefighter problem in which defence also spreads. Some approximation results are already known for this problem; we provide algorithmic and hardness results, as well as containment results for the infinite $n$-dimensional Cartesian and strong grid graphs.

Authors: Jessica Enright, Melissa A. Huggan, Ethan Hunter-Frankland, Margaret-Ellen Messinger, Dylan Pearson

The Firefighter Problem models a spreading process (originally a fire, alternatively an infection or rumour, for example) on a graph. A defender saves a single vertex per turn; after each defence, the fire spreads to the unburned and undefended neighbours of all burning vertices. Deciding whether a strategy exists for the defender to protect some targeted number of vertices is computationally hard in graphs in general, but tractable in some restricted cases. Inspired by research into spreadable rabies vaccines for bats, we study a variant of the Firefighter problem in which defence also spreads. Some approximation results are already known for this problem; we provide algorithmic and hardness results, as well as containment results for the infinite $n$-dimensional Cartesian and strong grid graphs.

Tuesday, October 06 2026, 00:00

Guanaco: A Global-Uniformity Algorithm for Near-Submodular-Width Conjunctive Query Evaluation

Authors: Mahmoud Abo Khamis, Hubie Chen

We present Guanaco, an algorithm for performing conjunctive query evaluation where, for each Boolean conjunctive query, and positive epsilon, the algorithm achieves polynomial time with exponent equal to the submodular width plus epsilon. The algorithm and its running time generalize smoothly to general conjunctive queries. We believe the algorithm and its analysis to be notably simple, indeed, together we believe they form a highly simple argument that conjunctive query evaluation can be performed in essentially submodular width time. In the case of Boolean conjunctive queries, the algorithm is based on interleaving three simple primitives: a subroutine for establishing a form of consistency; a subroutine for establishing global uniformity, which, briefly speaking, partitions relations as needed to control discrepancies between average degree and maximum degree; and, a simple step that joins pairs of existing relations to form new relations.

Authors: Mahmoud Abo Khamis, Hubie Chen

We present Guanaco, an algorithm for performing conjunctive query evaluation where, for each Boolean conjunctive query, and positive epsilon, the algorithm achieves polynomial time with exponent equal to the submodular width plus epsilon. The algorithm and its running time generalize smoothly to general conjunctive queries. We believe the algorithm and its analysis to be notably simple, indeed, together we believe they form a highly simple argument that conjunctive query evaluation can be performed in essentially submodular width time. In the case of Boolean conjunctive queries, the algorithm is based on interleaving three simple primitives: a subroutine for establishing a form of consistency; a subroutine for establishing global uniformity, which, briefly speaking, partitions relations as needed to control discrepancies between average degree and maximum degree; and, a simple step that joins pairs of existing relations to form new relations.

Tuesday, October 06 2026, 00:00

CT-Miner: Fast and Coarse-Grained Time-Series Pattern Mining via Cartesian Trees

Authors: Hyundong Jin, Hyunki Hong, Yo-Sub Han

Time series often contain recurring structural patterns, and efficiently mining such patterns into compact representations is essential for scalable analysis of long sequences. Cartesian tree (CT) equivalence provides a well-established structural abstraction that preserves hierarchical order structure while discarding exact values and fine-grained ordinal variations. By grouping multiple ordinal patterns into a shared structural form, CT equivalence offers a principled way to compress recurring temporal structure. However, mining frequent CT-equivalent patterns at scale remains computationally expensive. A naive pairwise approach repeatedly constructs and counts CT representations over subsequences, requiring $O(n^4)$ time for a sequence of length $n$, which severely limits its applicability to long sequences. We propose a new Cartesian pattern mining algorithm based on a Cartesian suffix tree that compactly organizes CT-equivalent subsequences and reuses shared structural information. Our method reduces exhaustive CT-pattern occurrence collection from $O(n^4)$ to $O(n^2)$ time, and we formally prove the correctness and complexity bounds. We further show that this computational gain translates into effective compact representations. Across diverse time-series datasets, a small set of mined CT patterns preserves meaningful clustering structure, and comparisons with finer-grained order-preserving representations show that CT equivalence reduces redundant ordinal distinctions under limited feature budgets. Our implementation is available at github.com/hyundong98/CT-Miner .

Authors: Hyundong Jin, Hyunki Hong, Yo-Sub Han

Time series often contain recurring structural patterns, and efficiently mining such patterns into compact representations is essential for scalable analysis of long sequences. Cartesian tree (CT) equivalence provides a well-established structural abstraction that preserves hierarchical order structure while discarding exact values and fine-grained ordinal variations. By grouping multiple ordinal patterns into a shared structural form, CT equivalence offers a principled way to compress recurring temporal structure. However, mining frequent CT-equivalent patterns at scale remains computationally expensive. A naive pairwise approach repeatedly constructs and counts CT representations over subsequences, requiring $O(n^4)$ time for a sequence of length $n$, which severely limits its applicability to long sequences. We propose a new Cartesian pattern mining algorithm based on a Cartesian suffix tree that compactly organizes CT-equivalent subsequences and reuses shared structural information. Our method reduces exhaustive CT-pattern occurrence collection from $O(n^4)$ to $O(n^2)$ time, and we formally prove the correctness and complexity bounds. We further show that this computational gain translates into effective compact representations. Across diverse time-series datasets, a small set of mined CT patterns preserves meaningful clustering structure, and comparisons with finer-grained order-preserving representations show that CT equivalence reduces redundant ordinal distinctions under limited feature budgets. Our implementation is available at https://github.com/hyundong98/CT-Miner .

Tuesday, October 06 2026, 00:00

Multilevel Dynamic Thinning for Matroid Secretary

Authors: Dennis Joyce

In the matroid secretary problem, weighted elements arrive in random order, and an online algorithm must irrevocably accept elements forming a high-weight independent set. Dynamic Thinning is a recent, conceptually simple $3.1462$-competitive algorithm for the matroid secretary problem that maintains a random reference set. Given this reference set, the elements in its maximum-weight independent subset have been accepted independently with a time-dependent probability. We extend this approach by replacing the single reference set with a finite hierarchy of nested reference sets. For every fixed $\eps>0$, the resulting algorithm is $(e+\eps)$-probability-competitive for arbitrary matroids, with $O_\eps(n^2)$ queries in the worst case.

Authors: Dennis Joyce

In the matroid secretary problem, weighted elements arrive in random order, and an online algorithm must irrevocably accept elements forming a high-weight independent set. Dynamic Thinning is a recent, conceptually simple $3.1462$-competitive algorithm for the matroid secretary problem that maintains a random reference set. Given this reference set, the elements in its maximum-weight independent subset have been accepted independently with a time-dependent probability. We extend this approach by replacing the single reference set with a finite hierarchy of nested reference sets. For every fixed $\eps>0$, the resulting algorithm is $(e+\eps)$-probability-competitive for arbitrary matroids, with $O_\eps(n^2)$ queries in the worst case.

Tuesday, October 06 2026, 00:00

A Factor-5 Conversion to Internal Collage Systems

Authors: Simone Faro

A collage system is a grammar-based compression model that extends straight-line programs with repetition and substring truncation. Internal collage systems additionally require every nonterminal to be structurally reachable from the start symbol. Migita, Uehata, and I (CPM 2026) showed that any collage system of size $m$ can be converted into an internal one generating the same string with size at most $9m$, and left the improvement of this constant as an open problem. We show that a simple refinement of their top-down conversion reduces the bound to $5m$. The proof combines three elementary ideas: canonicalization of generated truncations that remain aligned with a target endpoint; a repetition decomposition that absorbs every complete copy of the repetition base into a maximal core; and monotonicity of structural reachability, which prevents an input truncation rule from both becoming structurally reachable and later acting as a hidden target at which endpoint alignment is lost. The conversion runs in deterministic $O(m^2)$ worst-case time in the stated unit-cost random-access machine model. Consequently, for every string, the minimum size of an internal collage system is at most five times the minimum size of a general collage system.

Authors: Simone Faro

A collage system is a grammar-based compression model that extends straight-line programs with repetition and substring truncation. Internal collage systems additionally require every nonterminal to be structurally reachable from the start symbol. Migita, Uehata, and I (CPM 2026) showed that any collage system of size $m$ can be converted into an internal one generating the same string with size at most $9m$, and left the improvement of this constant as an open problem. We show that a simple refinement of their top-down conversion reduces the bound to $5m$. The proof combines three elementary ideas: canonicalization of generated truncations that remain aligned with a target endpoint; a repetition decomposition that absorbs every complete copy of the repetition base into a maximal core; and monotonicity of structural reachability, which prevents an input truncation rule from both becoming structurally reachable and later acting as a hidden target at which endpoint alignment is lost. The conversion runs in deterministic $O(m^2)$ worst-case time in the stated unit-cost random-access machine model. Consequently, for every string, the minimum size of an internal collage system is at most five times the minimum size of a general collage system.

Tuesday, October 06 2026, 00:00

Exact Optimal Transport by Matching

Authors: Dmitry Kamenetsky

Balanced discrete optimal transport between n sources and n targets of unit mass is exactly the minimum-cost assignment problem-a bipartite perfect matching-and is therefore solvable exactly by industrial matching engines in milliseconds to seconds. We ask when the exact approach beats the standard approximate alternatives, entropic Sinkhorn and its accelerated variant Greenkhorn, and make the sparse-exact side certified by a textbook LP dual-feasibility clip. Three contributions. (i) Measurement: on dense 2-D instances, exact matching (Jonker-Volgenant) is faster and strictly more accurate than either approximate method throughout the moderate-n regime (0.01 s at n=500 to 11.5 s at n=8000); reaching a 1% quality target on the same hardware requires roughly 10-80 min for Greenkhorn (factors 4e2-6e4 over exact; plain Sinkhorn is 20-650x slower still), a rough power-law projection beyond the measured range. Greenkhorn's measured speedup over plain Sinkhorn is only 1.0-1.5x on most converged cells. (ii) A simple kNN-pool gap certificate: given a pool matching and its Blossom dual, a one-pass O(n^2) clip produces a dense-feasible lower bound; combined with the Sinkhorn dual potential (valid at every iterate, not just at convergence), the bound is valid on all 45 measured configurations and tightens monotonically with k. (iii) A multi-robot task-allocation sanity check where the discrete plan is the deliverable: per-round exact assignment costs 0.1-68 ms, while a Sinkhorn-plus-hardening pipeline costs 0.12-15.9 s and accumulates 6-27% extra travel over 15 rounds. The Sinkhorn family's large-n dense regime is acknowledged and left untouched. Code, data, and results under MIT: github.com/dimkadimon/OT-Blossom.

Authors: Dmitry Kamenetsky

Balanced discrete optimal transport between n sources and n targets of unit mass is exactly the minimum-cost assignment problem-a bipartite perfect matching-and is therefore solvable exactly by industrial matching engines in milliseconds to seconds. We ask when the exact approach beats the standard approximate alternatives, entropic Sinkhorn and its accelerated variant Greenkhorn, and make the sparse-exact side certified by a textbook LP dual-feasibility clip. Three contributions. (i) Measurement: on dense 2-D instances, exact matching (Jonker-Volgenant) is faster and strictly more accurate than either approximate method throughout the moderate-n regime (0.01 s at n=500 to 11.5 s at n=8000); reaching a 1% quality target on the same hardware requires roughly 10-80 min for Greenkhorn (factors 4e2-6e4 over exact; plain Sinkhorn is 20-650x slower still), a rough power-law projection beyond the measured range. Greenkhorn's measured speedup over plain Sinkhorn is only 1.0-1.5x on most converged cells. (ii) A simple kNN-pool gap certificate: given a pool matching and its Blossom dual, a one-pass O(n^2) clip produces a dense-feasible lower bound; combined with the Sinkhorn dual potential (valid at every iterate, not just at convergence), the bound is valid on all 45 measured configurations and tightens monotonically with k. (iii) A multi-robot task-allocation sanity check where the discrete plan is the deliverable: per-round exact assignment costs 0.1-68 ms, while a Sinkhorn-plus-hardening pipeline costs 0.12-15.9 s and accumulates 6-27% extra travel over 15 rounds. The Sinkhorn family's large-n dense regime is acknowledged and left untouched. Code, data, and results under MIT: https://github.com/dimkadimon/OT-Blossom.

Tuesday, October 06 2026, 00:00

Optimal Convergence of Iterative Methods for Datalogo

Authors: Simon Frisk, Sungjin Im, Paraschos Koutris, Benjamin Moseley, Hung Ngo, Kirk Pruhs, Hangdong Zhao

$\mathsf{Datalog}^\circ$ has been introduced as an extension to Datalog that increases expressiveness, yet retains simple least fixpoint semantics and admits optimization techniques such as semi-naïve evaluation and demand transformation. $\mathsf{Datalog}^\circ$ accomplishes this by generalizing the {\em or} and {\em and} operators of Datalog to addition and multiplication over a semiring. Finding a (minimal) fixpoint of a $\mathsf{Datalog}^\circ$ program is equivalent to finding a solution to a system of polynomial equations over the underlying semiring. Solving these systems of polynomial equations is not only a fundamental problem in the theory of $\mathsf{Datalog}^\circ$, but also has many applications in computer science, such as in databases, program analysis, and optimization. This paper resolves a key open problem in the theory of $\mathsf{Datalog}^\circ$: we prove a tight upper bound on the number of steps until convergence of iterative methods for solving these polynomial equation systems over a commutative $p$-stable semiring. In particular, we show that the number of steps until convergence is $O((p+1)n)$ where $n$ is the output size of the $\mathsf{Datalog}^\circ$ program. As the number of steps until convergence is only a proxy for the runtime of $\mathsf{Datalog}^\circ$ evaluation, we also consider the number of semiring operations used and show that, for a natural class of algorithms, $O((p+1)mn)$ is a tight upper bound, where $m$ is the maximum number of semiring operations per iteration.

Authors: Simon Frisk, Sungjin Im, Paraschos Koutris, Benjamin Moseley, Hung Ngo, Kirk Pruhs, Hangdong Zhao

$\mathsf{Datalog}^\circ$ has been introduced as an extension to Datalog that increases expressiveness, yet retains simple least fixpoint semantics and admits optimization techniques such as semi-naïve evaluation and demand transformation. $\mathsf{Datalog}^\circ$ accomplishes this by generalizing the {\em or} and {\em and} operators of Datalog to addition and multiplication over a semiring. Finding a (minimal) fixpoint of a $\mathsf{Datalog}^\circ$ program is equivalent to finding a solution to a system of polynomial equations over the underlying semiring. Solving these systems of polynomial equations is not only a fundamental problem in the theory of $\mathsf{Datalog}^\circ$, but also has many applications in computer science, such as in databases, program analysis, and optimization. This paper resolves a key open problem in the theory of $\mathsf{Datalog}^\circ$: we prove a tight upper bound on the number of steps until convergence of iterative methods for solving these polynomial equation systems over a commutative $p$-stable semiring. In particular, we show that the number of steps until convergence is $O((p+1)n)$ where $n$ is the output size of the $\mathsf{Datalog}^\circ$ program. As the number of steps until convergence is only a proxy for the runtime of $\mathsf{Datalog}^\circ$ evaluation, we also consider the number of semiring operations used and show that, for a natural class of algorithms, $O((p+1)mn)$ is a tight upper bound, where $m$ is the maximum number of semiring operations per iteration.

Tuesday, October 06 2026, 00:00

Geometry-Dependent Approximation for Non-Monotone $k$-Submodular Maximization

Authors: Vaneet Aggarwal

We study nonnegative, non-monotone $k$-submodular maximization with $k\ge2$ labels under support constraints, and show how the certified approximation coefficient improves as the support region permits more uniform selection. For a compact convex down-closed support region $P\subseteq[0,1]^n$, the diagonal level $ζ(P)=\max\{t\in[0,1]:t {\bf 1} \in P\}$ ranges from $ζ=0$, which carries no geometric promise, to $ζ=1$, which is unrestricted support. Our main structural result is a comparator-uniform linearization of the multilinear extension, built from an objective-independent action and a comparator-independent update field. For $k\ge3$, its validity reduces, independently of the number of elements, to four polynomial inequalities of degree at most three in one or two variables, only one of which depends on $k$. Explicit parameter choices give a nondecreasing certified profile $\underlineα_k(ζ)$, in closed form on all of $[0,1]$ when $k=2$. At $ζ=0$ we certify $0.4456\ldots$ for $k=2$ and $0.4541\ldots$ for every $k\ge3$, improving the recent $\sqrt2-1$ guarantee for one matroid or one knapsack, as well as the $1/3$-type guarantees for a fixed number of budgets; at $ζ=1$ we certify $1/2$ for $k=2$, $(\sqrt{17}-3)/2$ for $k=3,4$, and $k/(2k-1)$ for $k\ge5$, whose excess over $1/2$ is of order $1/k$ rather than the previous $1/k^2$. Value-retaining rounding transfers these guarantees to matroid and knapsack constraints, and the same field yields $O(\sqrt T)$ approximate regret online under gradient or post-decision value feedback.

Authors: Vaneet Aggarwal

We study nonnegative, non-monotone $k$-submodular maximization with $k\ge2$ labels under support constraints, and show how the certified approximation coefficient improves as the support region permits more uniform selection. For a compact convex down-closed support region $P\subseteq[0,1]^n$, the diagonal level $ζ(P)=\max\{t\in[0,1]:t {\bf 1} \in P\}$ ranges from $ζ=0$, which carries no geometric promise, to $ζ=1$, which is unrestricted support. Our main structural result is a comparator-uniform linearization of the multilinear extension, built from an objective-independent action and a comparator-independent update field. For $k\ge3$, its validity reduces, independently of the number of elements, to four polynomial inequalities of degree at most three in one or two variables, only one of which depends on $k$. Explicit parameter choices give a nondecreasing certified profile $\underlineα_k(ζ)$, in closed form on all of $[0,1]$ when $k=2$. At $ζ=0$ we certify $0.4456\ldots$ for $k=2$ and $0.4541\ldots$ for every $k\ge3$, improving the recent $\sqrt2-1$ guarantee for one matroid or one knapsack, as well as the $1/3$-type guarantees for a fixed number of budgets; at $ζ=1$ we certify $1/2$ for $k=2$, $(\sqrt{17}-3)/2$ for $k=3,4$, and $k/(2k-1)$ for $k\ge5$, whose excess over $1/2$ is of order $1/k$ rather than the previous $1/k^2$. Value-retaining rounding transfers these guarantees to matroid and knapsack constraints, and the same field yields $O(\sqrt T)$ approximate regret online under gradient or post-decision value feedback.

Tuesday, October 06 2026, 00:00

Conjunctive Queries with Negation: Beyond Signed-Acyclicity

Authors: Simon Frisk, Paraschos Koutris

We study constant-delay enumeration for conjunctive queries with negation ($\texttt{CQ}^{\neg}$). Prior work defined \emph{signed-acyclicity}, which characterizes the class of queries where linear preprocessing time is achievable, but little has been known beyond this. We introduce a new hypergraph width measure for $\texttt{CQ}^{\neg}$, the \emph{signed fractional hypertree width} ($\textsf{sfhw}$), defined by requiring that a single variable order simultaneously handle every subset of the negative atoms. We show that $\textsf{sfhw}$ strictly generalizes signed-acyclicity (recovered when $\textsf{sfhw} = 1$) and fractional hypertree width (recovered on queries without negation). Our main algorithmic result is a variable-elimination algorithm that achieves constant-delay enumeration on input $I$ for any full $\texttt{CQ}^{\neg}$ query with preprocessing time $O(|I|^{\textsf{sfhw}})$. We further show that using multiple variable orders can improve this bound, exhibiting an $O(|I|^{3/2})$ algorithm for $k$-cycle queries with at least one negative edge.

Authors: Simon Frisk, Paraschos Koutris

We study constant-delay enumeration for conjunctive queries with negation ($\texttt{CQ}^{\neg}$). Prior work defined \emph{signed-acyclicity}, which characterizes the class of queries where linear preprocessing time is achievable, but little has been known beyond this. We introduce a new hypergraph width measure for $\texttt{CQ}^{\neg}$, the \emph{signed fractional hypertree width} ($\textsf{sfhw}$), defined by requiring that a single variable order simultaneously handle every subset of the negative atoms. We show that $\textsf{sfhw}$ strictly generalizes signed-acyclicity (recovered when $\textsf{sfhw} = 1$) and fractional hypertree width (recovered on queries without negation). Our main algorithmic result is a variable-elimination algorithm that achieves constant-delay enumeration on input $I$ for any full $\texttt{CQ}^{\neg}$ query with preprocessing time $O(|I|^{\textsf{sfhw}})$. We further show that using multiple variable orders can improve this bound, exhibiting an $O(|I|^{3/2})$ algorithm for $k$-cycle queries with at least one negative edge.

Tuesday, October 06 2026, 00:00

Vertex Cover Problem with Advice

Authors: Lucas de Oliveira Silva, Lehilton Lelis Chaves Pedrosa

We study the minimum Vertex Cover problem under two non-adaptive offline advice models, where predictions about a fixed optimum solution are provided once as part of the input. These forms of prediction were introduced independently by Cohen-Addad, d'Orsi, Gupta, Lee, and Panigrahi (2024) and by Ghoshal, Makarychev, and Makarychev (2025). In Partial Predictions, independently revealed vertices come with correct membership labels. For every sufficiently small fixed $\varepsilon>0$, we give a randomized polynomial-time algorithm that has expected approximation ratio at most $2-(2-o(1))\frac{\log\log(1/\varepsilon)}{\log(1/\varepsilon)}$. In Noisy Predictions, every vertex instead receives a mutually independent noisy membership label of bias $\varepsilon$. For every sufficiently small fixed $\varepsilon>0$, we give a randomized polynomial-time algorithm that has expected approximation ratio at most $2-(1-o(1))\frac{\log\log(1/\varepsilon)}{\log(1/\varepsilon)}$. Our Noisy Predictions bound matches the leading asymptotic improvement below $2$ obtained by Aamand, Chen, Gollapudi, Silwal, and Wu (2025), despite using only one noisy label per vertex rather than a separate independent label for each endpoint of each incident edge. Both our bounds hold as $\varepsilon$ goes to $0$ and are strictly below $2$, the optimal approximation threshold for minimum Vertex Cover without advice under the Unique Games Conjecture, as shown by Khot and Regev (2008).

Authors: Lucas de Oliveira Silva, Lehilton Lelis Chaves Pedrosa

We study the minimum Vertex Cover problem under two non-adaptive offline advice models, where predictions about a fixed optimum solution are provided once as part of the input. These forms of prediction were introduced independently by Cohen-Addad, d'Orsi, Gupta, Lee, and Panigrahi (2024) and by Ghoshal, Makarychev, and Makarychev (2025). In Partial Predictions, independently revealed vertices come with correct membership labels. For every sufficiently small fixed $\varepsilon>0$, we give a randomized polynomial-time algorithm that has expected approximation ratio at most $2-(2-o(1))\frac{\log\log(1/\varepsilon)}{\log(1/\varepsilon)}$. In Noisy Predictions, every vertex instead receives a mutually independent noisy membership label of bias $\varepsilon$. For every sufficiently small fixed $\varepsilon>0$, we give a randomized polynomial-time algorithm that has expected approximation ratio at most $2-(1-o(1))\frac{\log\log(1/\varepsilon)}{\log(1/\varepsilon)}$. Our Noisy Predictions bound matches the leading asymptotic improvement below $2$ obtained by Aamand, Chen, Gollapudi, Silwal, and Wu (2025), despite using only one noisy label per vertex rather than a separate independent label for each endpoint of each incident edge. Both our bounds hold as $\varepsilon$ goes to $0$ and are strictly below $2$, the optimal approximation threshold for minimum Vertex Cover without advice under the Unique Games Conjecture, as shown by Khot and Regev (2008).

Tuesday, October 06 2026, 00:00

Tarski Fixed Points in Quasi-FPT Queries

Authors: Xi Chen, Ruiquan Gao, Yuhao Li, Aviad Rubinstein, Mihalis Yannakakis

We study the query complexity of finding a Tarski fixed point over $[n]^k$. Previous work has left a large gap between $\smash{Ω(\log^2 n)}$ and $\smash{\log^{O(k)}n}$. We show that both of the previous upper and lower bounds were far from tight: for every $k\geq 3$, \[ Ω\left((\log n)^{\frac{1}{2}\lceil \log k\rceil}\right)\le \operatorname{Tarski}(n,k)\le O\left(5^k(\log n)^{\lceil \log k\rceil}\right). \] Succinctly, up to the fixed-parameter factor of $5^k$, the complexity is settled at $(\log n)^{Θ(\log k )}$. In particular, we obtain the first super-polynomial query lower bound for this problem.

Authors: Xi Chen, Ruiquan Gao, Yuhao Li, Aviad Rubinstein, Mihalis Yannakakis

We study the query complexity of finding a Tarski fixed point over $[n]^k$. Previous work has left a large gap between $\smash{Ω(\log^2 n)}$ and $\smash{\log^{O(k)}n}$. We show that both of the previous upper and lower bounds were far from tight: for every $k\geq 3$, \[ Ω\left((\log n)^{\frac{1}{2}\lceil \log k\rceil}\right)\le \operatorname{Tarski}(n,k)\le O\left(5^k(\log n)^{\lceil \log k\rceil}\right). \] Succinctly, up to the fixed-parameter factor of $5^k$, the complexity is settled at $(\log n)^{Θ(\log k )}$. In particular, we obtain the first super-polynomial query lower bound for this problem.

Tuesday, October 06 2026, 00:00

Nearly optimal Personalized PageRank computation

Authors: Rong-Hua Li, Yichun Yang, Junjie Zhou

We study the fundamental problem of computing Personalized PageRank (PPR) on an undirected and unweighted graph $G$. We focus on the $\eps$-error guarantee introduced by Andersen, Chung, and Lang [ACL; FOCS 2006 $\&$ Internet Math 2007]. Their classic local push method computes an approximate PPR vector satisfying the ACL $\eps$-error guarantee in $O((α\eps)^{-1})$ time, where $α$ is the teleportation parameter. In this paper, we eliminate the dependence on $α$ and present an algorithm that achieves the same error guarantee in $O(\eps^{-1-o(1)})$ time. Consequently, we obtain a nearly optimal algorithm for PPR computation under the ACL error guarantee, and a nearly linear algorithm for local graph clustering with complexity independent of $φ$.

Authors: Rong-Hua Li, Yichun Yang, Junjie Zhou

We study the fundamental problem of computing Personalized PageRank (PPR) on an undirected and unweighted graph $G$. We focus on the $\eps$-error guarantee introduced by Andersen, Chung, and Lang [ACL; FOCS 2006 $\&$ Internet Math 2007]. Their classic local push method computes an approximate PPR vector satisfying the ACL $\eps$-error guarantee in $O((α\eps)^{-1})$ time, where $α$ is the teleportation parameter. In this paper, we eliminate the dependence on $α$ and present an algorithm that achieves the same error guarantee in $O(\eps^{-1-o(1)})$ time. Consequently, we obtain a nearly optimal algorithm for PPR computation under the ACL error guarantee, and a nearly linear algorithm for local graph clustering with complexity independent of $φ$.

Tuesday, October 06 2026, 00:00

A Potential Function Analysis of Double Coverage for the $k$-Taxi Problem on Trees

Authors: Ali Karim Lalani

We provide potential function proofs of the competitive ratios of DoubleCoverage for the hard $k$-taxi problem on HSTs and general weighted trees of bounded depth. Buchbinder, Coester, and Naor (2023) obtained these ratios using time-reverse dual fitting and noted that they did not know a pure potential proof beyond $k=2$. We observe that the minimum matching distance between the online and offline taxi configurations can be expressed as an integral over the rooted tree of the absolute difference between their taxi counts below each point. This representation lets us analyse DoubleCoverage over short movement intervals and apply the resulting estimates to potentials that remain unchanged when both serving taxis are relocated from pickup to destination.

Authors: Ali Karim Lalani

We provide potential function proofs of the competitive ratios of DoubleCoverage for the hard $k$-taxi problem on HSTs and general weighted trees of bounded depth. Buchbinder, Coester, and Naor (2023) obtained these ratios using time-reverse dual fitting and noted that they did not know a pure potential proof beyond $k=2$. We observe that the minimum matching distance between the online and offline taxi configurations can be expressed as an integral over the rooted tree of the absolute difference between their taxi counts below each point. This representation lets us analyse DoubleCoverage over short movement intervals and apply the resulting estimates to potentials that remain unchanged when both serving taxis are relocated from pickup to destination.

Tuesday, October 06 2026, 00:00

TR26-230 | Robust subspace designs and the power of a unique small quantum witness | Simon Apers, Roman Edenhofer, Benjamin Mathieu-Bloise, Partha Mukhopadhyay

from ECCC Papers

The concept of subspace designs was introduced by Guruswami and Xing (STOC'13), and explicit constructions were given by Guruswami and Kopparty (FOCS'13). These are families of subspaces that have small intersection with any given subspace of a fixed dimension. We introduce \emph{robust subspace designs}. Informally, these are a quantitative extension in which we demand that not too many subspaces of the family contain directions that lie \emph{close} to any given subspace of a fixed dimension. We give a probabilistic construction of such a robust subspace design of polynomial size, as well as a non-trivial explicit construction of superpolynomial size. Our main application of this new concept is a quantum space-bounded variant of the Valiant-Vazirani theorem (Theor.~Comput.~Sci.'86), which shows that restricting $\mathsf{NP}$-complete problems to instances with at most one accepting witness preserves hardness under randomized reductions. For quantum witnesses, the analogous quantity is the dimension of an accepting witness subspace. We use our probabilistic construction of robust subspace designs to isolate a unique witness for space-bounded quantum Merlin-Arthur protocols with perfect completeness and an acceptance gap outside their perfectly accepting subspace. As a further application, we give a randomized reduction of well-conditioned nullity testing to space-bounded quantum Merlin-Arthur protocols with perfect completeness. Using a similar idea, we find that ordinary subspace designs allow us to recover the classical $C_= L}$ containment of Allender, Beals, and Ogihara (STOC'96) for general nullity testing through a simpler proof.

Monday, October 05 2026, 20:17

TR26-229 | A polynomial scaling window for random $k$-SAT and a proof of the satisfiability conjecture | Gaia Carenini

from ECCC Papers

We prove that the scaling window of random $k$-SAT has width $O(n^{1/2+1/k})$, a polynomial improvement over our previous bound of $O(n/\log n)$. Combined with a result of Abbe and Montanari, this establishes the satisfiability conjecture for every fixed $k\geq 3$.

Monday, October 05 2026, 14:04

QuICS Hartree Postdoctoral Fellowships at Joint Center for Quantum Information and Computer Science (QuICS) at QuICS/University of Maryland (apply by December 1, 2026)

from CCI: jobs

The Joint Center for Quantum Information and Computer Science (QuICS, quics.umd.edu) is seeking exceptional candidates for the QuICS Hartree Postdoctoral Fellowships in Quantum Information and Computer Science. Apply at: umd.wd1.myworkdayjobs.com/en-US/UMCP/job/QuICS-Hartree-Postdoctoral-Fellow-1_JR104987 Website: umd.wd1.myworkdayjobs.com/en-US/UMCP/job/QuICS-Hartree-Postdoctoral-Fellow-1_JR104987 Email: quics-coordinator@umiacs.umd.edu

The Joint Center for Quantum Information and Computer Science (QuICS, http://quics.umd.edu) is seeking exceptional candidates for the QuICS Hartree Postdoctoral Fellowships in Quantum Information and Computer Science. Apply at: https://umd.wd1.myworkdayjobs.com/en-US/UMCP/job/QuICS-Hartree-Postdoctoral-Fellow-1_JR104987

Website: https://umd.wd1.myworkdayjobs.com/en-US/UMCP/job/QuICS-Hartree-Postdoctoral-Fellow-1_JR104987
Email: quics-coordinator@umiacs.umd.edu

By shacharlovett

Monday, October 05 2026, 13:59

A Theory of Nested Cascading in Directed Logic

Authors: Ihar Babushkin, Oliver Melchert, Ayhan Demircan, Uwe Morgner

In directed logic (DL), electronically controlled optical elements serve as photonic gates. Such electro-optical elements are of mixed nature: they have two inputs--electronic and optical--but only one, optical, output. This makes cascading such gates without repeated conversion between optical and electronic representations cumbersome. This problem can be largely overcome using the nested cascading scheme proposed by Shamir and Hardy [Opt. Express, 17, 150 (2007)]. Although promising as a solution to the cascading problem, the Shamir-Hardy scheme has so far been proved or implemented only for a few simplest cases. Here, we develop a general rigorous theory of nested cascading, valid for an arbitrary number of gates. We propose a variant of the algorithm which easily extendable to large number of gates, and rigorously prove its validity. Furthermore, we analyze how nested cascading scales with the size of the corresponding Boolean formula. We show that good (linear) scalability is guaranteed in many important cases, while the average scaling with respect to the corresponding Boolean formulas is only moderately polynomial, with an exponent of approximately 3/2. Yet, the worst-case scaling remains exponential with respect to more general Boolean circuits allowing sharing and reuse of intermediate results.

Authors: Ihar Babushkin, Oliver Melchert, Ayhan Demircan, Uwe Morgner

In directed logic (DL), electronically controlled optical elements serve as photonic gates. Such electro-optical elements are of mixed nature: they have two inputs--electronic and optical--but only one, optical, output. This makes cascading such gates without repeated conversion between optical and electronic representations cumbersome. This problem can be largely overcome using the nested cascading scheme proposed by Shamir and Hardy [Opt. Express, 17, 150 (2007)]. Although promising as a solution to the cascading problem, the Shamir-Hardy scheme has so far been proved or implemented only for a few simplest cases. Here, we develop a general rigorous theory of nested cascading, valid for an arbitrary number of gates. We propose a variant of the algorithm which easily extendable to large number of gates, and rigorously prove its validity. Furthermore, we analyze how nested cascading scales with the size of the corresponding Boolean formula. We show that good (linear) scalability is guaranteed in many important cases, while the average scaling with respect to the corresponding Boolean formulas is only moderately polynomial, with an exponent of approximately 3/2. Yet, the worst-case scaling remains exponential with respect to more general Boolean circuits allowing sharing and reuse of intermediate results.

Monday, October 05 2026, 00:00

The complexity of entangled graph colouring via polymorphisms

Authors: Eric Culf

Constraint satisfaction problems (CSPs) with operator assignments to the variables provide a well-structured setting to study the decision complexity of the entangled value of classes of nonlocal games. Due to the CSP dichotomy theorem, the complexity of constraint satisfaction problems with classical assignments can be fully understood by studying the symmetries of the CSP, in terms of the polymorphisms of the underlying relational structure. In this work, we show that the polymorphism-based reductions between CSPs can be generalised to gap-preserving reductions between entangled CSPs based on an entangled analogue of the polymorphisms. This reduction allows us to show undecidability of entangled graph colouring with more than three colours, a problem that has proved resistant to prior hardness reductions based on commutativity gadgets.

Authors: Eric Culf

Constraint satisfaction problems (CSPs) with operator assignments to the variables provide a well-structured setting to study the decision complexity of the entangled value of classes of nonlocal games. Due to the CSP dichotomy theorem, the complexity of constraint satisfaction problems with classical assignments can be fully understood by studying the symmetries of the CSP, in terms of the polymorphisms of the underlying relational structure. In this work, we show that the polymorphism-based reductions between CSPs can be generalised to gap-preserving reductions between entangled CSPs based on an entangled analogue of the polymorphisms. This reduction allows us to show undecidability of entangled graph colouring with more than three colours, a problem that has proved resistant to prior hardness reductions based on commutativity gadgets.

Monday, October 05 2026, 00:00

How to Have a Sensitive Debate: An Instance-Optimal Protocol for AI Debate

Authors: Jiawei Li, Zhiyang Xun, Lijie Chen, Jonah Brown-Cohen

As powerful AI systems reach and sometimes surpass the abilities of human experts across a range of cognitively demanding tasks, the problem of accurate oversight and supervision of these systems has become increasingly urgent. One promising approach is AI debate, which seeks to leverage a debate between two powerful AIs to break complex questions down into simpler claims that can be easily judged directly. Theoretical work on debate has formalized this intuition in the language of computational complexity theory, where the goal is to design protocols (i.e., rules of the debate game) that provide rigorous guarantees on correctness for judging solutions to complex problems with limited supervision. Specifically, the current best protocol has been shown to work for all problems that have sufficiently stable decompositions into subproblems. In this paper, we design a new protocol for this same class of problems that improves on the prior work in several ways. First, correctness holds in a worst-case rather than an average-case sense. Second, being honest and correct is a dominant-strategy equilibrium for both debaters, rather than a Stackelberg equilibrium. Finally, we prove black-box lower bounds, showing that our new protocol is instance-wise optimal. That is, no protocol for this class of problems can outperform ours while making only black-box queries to human judgments. We obtain these results by relating the notion of stable problem decompositions to the concept of fractional block sensitivity from query complexity.

Authors: Jiawei Li, Zhiyang Xun, Lijie Chen, Jonah Brown-Cohen

As powerful AI systems reach and sometimes surpass the abilities of human experts across a range of cognitively demanding tasks, the problem of accurate oversight and supervision of these systems has become increasingly urgent. One promising approach is AI debate, which seeks to leverage a debate between two powerful AIs to break complex questions down into simpler claims that can be easily judged directly. Theoretical work on debate has formalized this intuition in the language of computational complexity theory, where the goal is to design protocols (i.e., rules of the debate game) that provide rigorous guarantees on correctness for judging solutions to complex problems with limited supervision. Specifically, the current best protocol has been shown to work for all problems that have sufficiently stable decompositions into subproblems. In this paper, we design a new protocol for this same class of problems that improves on the prior work in several ways. First, correctness holds in a worst-case rather than an average-case sense. Second, being honest and correct is a dominant-strategy equilibrium for both debaters, rather than a Stackelberg equilibrium. Finally, we prove black-box lower bounds, showing that our new protocol is instance-wise optimal. That is, no protocol for this class of problems can outperform ours while making only black-box queries to human judgments. We obtain these results by relating the notion of stable problem decompositions to the concept of fractional block sensitivity from query complexity.

Monday, October 05 2026, 00:00

Two-Sided Product Expanding Codes via Rademacher Matrices

Authors: Eshan Chattopadhyay, Noam Ringach, Nicholas Spooner

We give a proof of the existence of two-sided product expanding codes which, unlike the earlier result of Kalachev and Panteleev (FOCS, 2025), does not rely on explicit constructions of asymptotically optimal locally testable codes ($c^3$-LTCs). For every fixed number of component codes and dimensions whose rates are bounded away from zero and one, we show that independent random linear codes over a sufficiently large prime field have constant two-sided product expansion with probability tending to one. The tradeoff is that our proof requires the characteristic to grow with the block length, while [KP25] takes extensions of $\mathbb{F}_2$. To replace the use of $c^3$-LTCs, we develop several new techniques that we view as interesting in their own right. Instead of working directly over finite fields, we work over the reals and use random Rademacher matrices for the generator matrices of the component codes. From here, we we show that the extendability of $\varepsilon$-closed sets can be reduced to controlling the operator norm of sparse restrictions of carefully chosen Gram matrices. Applying the trace power method to bound this norm reduces to bounding the number of possible labelings of certain closed walks on bipartite graphs, which we bound using the sparsity of the operators and bounds on the number of equivalence classes of weak Wigner words from Anderson and Zeitouni (Probab. Theory Relat. Fields., 2006), which were originally applied to band matrices. Due to our techniques not relying on explicit $c^3$-LTCs, we believe that they form a promising starting point towards showing the existence of product expanding tensor codes where the component codes have non-trivial automorphism groups and coboundary expanding codes that could be used as the local codes of non-cubical complexes, such as simplicial complexes.

Authors: Eshan Chattopadhyay, Noam Ringach, Nicholas Spooner

We give a proof of the existence of two-sided product expanding codes which, unlike the earlier result of Kalachev and Panteleev (FOCS, 2025), does not rely on explicit constructions of asymptotically optimal locally testable codes ($c^3$-LTCs). For every fixed number of component codes and dimensions whose rates are bounded away from zero and one, we show that independent random linear codes over a sufficiently large prime field have constant two-sided product expansion with probability tending to one. The tradeoff is that our proof requires the characteristic to grow with the block length, while [KP25] takes extensions of $\mathbb{F}_2$. To replace the use of $c^3$-LTCs, we develop several new techniques that we view as interesting in their own right. Instead of working directly over finite fields, we work over the reals and use random Rademacher matrices for the generator matrices of the component codes. From here, we we show that the extendability of $\varepsilon$-closed sets can be reduced to controlling the operator norm of sparse restrictions of carefully chosen Gram matrices. Applying the trace power method to bound this norm reduces to bounding the number of possible labelings of certain closed walks on bipartite graphs, which we bound using the sparsity of the operators and bounds on the number of equivalence classes of weak Wigner words from Anderson and Zeitouni (Probab. Theory Relat. Fields., 2006), which were originally applied to band matrices. Due to our techniques not relying on explicit $c^3$-LTCs, we believe that they form a promising starting point towards showing the existence of product expanding tensor codes where the component codes have non-trivial automorphism groups and coboundary expanding codes that could be used as the local codes of non-cubical complexes, such as simplicial complexes.

Monday, October 05 2026, 00:00

Non-Malleable Affine Extractors with Small Error and Complexity Lower Bounds

Authors: Xin Li, Yan Zhong

We construct explicit non-malleable affine extractors for every constant entropy rate, with linear output length and exponentially small error, against any fixed number of affine tamperings without fixed points. For every fixed $0<η<1$ and $t$, we also obtain entropy threshold $C_{η,t}n/\log n$, output length $\lfloor n^{1-η}\rfloor$, and error $2^{-n^{1-η}}$ against $t$ tamperings. Our extractors, as well as the directional affine extractors of Li and Zhong (CCC 2024), yield explicit Boolean functions with correlation $2^{-Ω(n)}$ against weakly read-once linear branching programs of size $2^{Ω(n)}$. For non-oblivious decision trees, we prove linear depth lower bounds for queries of each fixed degree $r\ge2$. Applying Li's sumset extractor (FOCS 2023) gives depth $Ω_δ((n/\ell)\log\ell)$ for growing locality $\ell\le n^{1-δ}$, where $0<δ<1$ is fixed. In the same range, directional affine extractors give correlation $2^{-Ω(n/\sqrt\ell)}$ against local trees of depth $c(n/\ell)\log\ell/\log\log\ell$, for a sufficiently small constant $c>0$. Our extractors derandomize the lossless lifting of Efremenko and Itsykson (STOC 2026). For every fixed $0<ξ<1$, this gives explicit polynomial-size unsatisfiable CNFs on $N$ variables whose $\mathrm{Res}(\oplus)$ refutations of resolution depth at most $N$ require size at least $2^{(1-ξ)N}$. Separately, parity substitutions give polynomial-size CNFs on $N$ variables with polynomial-size ordinary-resolution proofs for which every $\mathrm{Res}(\oplus)$ refutation of size $S$ and depth $d$ satisfies $d\log(2S)=Ω(N^2)$. This removes the $\log^2 N$ loss in the tradeoff of Itsykson, Podolskii, and Shekhovtsov (CCC 2026).

Authors: Xin Li, Yan Zhong

We construct explicit non-malleable affine extractors for every constant entropy rate, with linear output length and exponentially small error, against any fixed number of affine tamperings without fixed points. For every fixed $0<η<1$ and $t$, we also obtain entropy threshold $C_{η,t}n/\log n$, output length $\lfloor n^{1-η}\rfloor$, and error $2^{-n^{1-η}}$ against $t$ tamperings. Our extractors, as well as the directional affine extractors of Li and Zhong (CCC 2024), yield explicit Boolean functions with correlation $2^{-Ω(n)}$ against weakly read-once linear branching programs of size $2^{Ω(n)}$. For non-oblivious decision trees, we prove linear depth lower bounds for queries of each fixed degree $r\ge2$. Applying Li's sumset extractor (FOCS 2023) gives depth $Ω_δ((n/\ell)\log\ell)$ for growing locality $\ell\le n^{1-δ}$, where $0<δ<1$ is fixed. In the same range, directional affine extractors give correlation $2^{-Ω(n/\sqrt\ell)}$ against local trees of depth $c(n/\ell)\log\ell/\log\log\ell$, for a sufficiently small constant $c>0$. Our extractors derandomize the lossless lifting of Efremenko and Itsykson (STOC 2026). For every fixed $0<ξ<1$, this gives explicit polynomial-size unsatisfiable CNFs on $N$ variables whose $\mathrm{Res}(\oplus)$ refutations of resolution depth at most $N$ require size at least $2^{(1-ξ)N}$. Separately, parity substitutions give polynomial-size CNFs on $N$ variables with polynomial-size ordinary-resolution proofs for which every $\mathrm{Res}(\oplus)$ refutation of size $S$ and depth $d$ satisfies $d\log(2S)=Ω(N^2)$. This removes the $\log^2 N$ loss in the tradeoff of Itsykson, Podolskii, and Shekhovtsov (CCC 2026).

Monday, October 05 2026, 00:00

Separating QMA from QCIP with a Classical Oracle, or, the Power of Quantum Proofs over Classical Interaction for Quantum Verifiers