arXane › Computer Science › Computer Science
Wednesday, 4 November 2026: 3 new papers, 12 cross-lists and 18 replacements in Discrete Mathematics (cs.DM), in arXiv's order, with full abstracts. The same papers as arXiv's own listing, set as a newspaper; every title links to arXiv.
A proper conflict-free coloring is a proper vertex coloring in which every non-isolated vertex has a neighbor whose color appears exactly once in its open neighborhood. We study this coloring on chordal and ordered bipartite graph classes. For well-partitioned chordal graphs, we prove the tight bound $\omega(G)\leq\pcf(G)\leq\omega(G)+1$ and give an $O(n^2)$ construction from a partition tree. Every assignment of lists of at least $\omega(G)+1$ colors also admits a PCF coloring that respects the lists. Deciding whether $\omega(G)$ colors suffice is NP-complete, even when the partition tree is a star. This also proves NP-completeness on chordal graphs when the number of colors is part of the input. For interval graphs, we prove that lists of size $\omega(G)+1$ always suffice, improving the previous ordinary-coloring bound of $\omega(G)+2$. We use matchings to characterize when $\omega(G)$ colors suffice and give an endpoint algorithm taking $2^{O(\omega(G)^2)}n^{O(1)}$ time. We also characterize the exact value when the clique number is at most three and give a linear-time algorithm from sorted interval endpoints. For biconvex graphs, we prove a tight five-color bound and give a direct exact algorithm taking $O(n^{33})$ time. For bipartite permutation graphs, a smaller dynamic program gives an exact $O(n^{17})$ algorithm. Finally, if a bipartite graph is convex over an ordered shore $X$, we prove the sharp bound $\pcf(G)\leq\lceil\log_2(|X|+1)\rceil+3$ and construct a coloring in linear time from the order.
In the random-pair Monte shuffle on $n$ cards, each step chooses two positions independently and uniformly and exchanges their cards with probability $1/2$. The chosen positions are public; the decisions to exchange cards remain hidden. We prove that the mixing time in expected conditional total variation distance is $2n\log n+O(n)$, with an exact leading constant and an $O(n)$ cutoff window. To our knowledge, this is the first public-schedule Monte shuffle whose full-permutation mixing time has been determined up to an additive $O(n)$ term. The upper bound follows by comparing two executions with the same public schedule to a classical random-transposition walk. For the lower bound, we construct a schedule-dependent test function and estimate its variance using a matrix-averaging operator. Combined with the depth bound of Czumaj and Lingas, the mixing estimate gives public switching networks with at most $2n\log n+O(n)$ switches and $O(\log n)$ depth for fixed error and failure probabilities. The author obtained this result through interaction with GPT-6 Astra.
A natural way to compare two graphs is to align their vertex sets by a bijection and to measure the difference of the aligned adjacency matrices in a matrix norm. Depending on the norm, this yields, for example, the edit distance, the cut distance, the spectral distance, and the local edit distance. To make these distances applicable to graphs of different order, one can consider blowups of the graphs or, equivalently, relax bijections to fractional alignments, that is, optimal transport plans between the uniform distributions on the vertex sets, in the spirit of Gromov-Wasserstein distances. We investigate how much the optimal transport versions can differ from their bijective counterparts, that is, we quantify their integrality gaps. For the edit distance, we improve the best known upper bound on the integrality gap from 3 to 2 and the lower bound from 6/5 to 4/3. For the cut distance, we approach Lov\'asz's conjecture that $\delta_\square \le 2\delta_\square^{OT}$ from both sides. We improve the previously best known upper bound $\delta_\square \le 32 \cdot (\delta_\square^{OT})^{1/67}$ (Borgs, Chayes, Lov\'asz, S\'os and Vesztergombi, Adv. Math. 2008) to $\delta_\square \le C_\varepsilon \cdot (\delta_\square^{OT})^{1-\varepsilon}$ for every $\varepsilon > 0$, and we construct graphs $G,H$ with $\delta_\square(G,H) = 2\delta_\square^{OT}(G,H)$, establishing a factor-2 lower bound that matches Lov\'asz's conjecture. For the local edit and spectral distances, we obtain upper bounds of order $\sqrt{t\ln(1/t)}$ and $\sqrt{t}$, respectively, where $t$ is the corresponding optimal transport distance, and we show that, unlike for the edit and cut distances, no linear upper bounds are possible. Finally, we show that computing the optimal transport distances is NP-hard, and we give hardness of approximation results for the cut, spectral, and local edit distances.
We show that the kissing numbers in dimensions 32, 33, 34, 35, 37, 38 and 39 are at least 352320, 370240, 390980, 415308, 499816, 605322 and 768916, improving the previous bounds 347584, 364736, 384836, 409676, 498024, 591900 and 763668. Except in dimension 38, the configurations are those of Edel, Rains and Sloane with new binary constant-weight codes of weight 8 and minimum distance 8 in the middle layer; each additional word adds 128 points. In dimension 38 we add 6855 antipodal pairs of vectors of the second shell of the Leech lattice to the empty equator of Kravatskiy's 591612-point configuration, where 144 pairs were known; this is an independent set problem in a regular graph of degree 11178 on 8386560 vertices. The codes and lines were found by local search, and all configurations were checked pair by pair in exact integer arithmetic.
A tournament is an orientation of a complete graph. A vertex $v$ controls a vertex $u\neq v$ if there is a directed path of length at most two from $v$ to $u$, and a $\delta$-king is one that controls at least $\delta(n-1)$ vertices. In the query complexity model, each query reveals the orientation of an edge. Shen, Sheng and Wu [SICOMP'03] established an $\Omega(n^{4/3})$ lower bound on the deterministic query complexity of finding a $1$-king, and a non-matching upper bound of $O(n^{3/2})$. Neither bound has been improved in over two decades, despite substantial progress on variants of the problem. For $\delta$-kings with $\delta < 1$, Biswas, Jayapaul, Raman and Satti [Discrete Applied Mathematics'22] showed that $O(n^{4/3})$ queries suffice to find a $\frac12$-king. Lachish, Reidl and Trehan [FSTTCS'22] improved this guarantee to $\frac12+\frac{2}{17}$ using $\widetilde{O}(n^{4/3})$ queries, and asked whether a larger fraction could be achieved within the same query bound. We answer this question affirmatively for every fixed fraction below one: for every fixed $\varepsilon\in(0,1)$, we give a deterministic algorithm that finds a $(1-\varepsilon)$-king using $O(n^{4/3})$ queries. The design of our algorithm is informed by a structural analysis combining a sparse regularity lemma due to Allen, Kohayakawa, Mota and Parente [Electronic Journal of Combinatorics'14] with a new sampling argument based on a reachability theorem of Afek, Gafni and Linial [arXiv'19].
We introduce a family of cut-sufficient instances for undirected multiflow that generalizes single-source planar and fully-planar instances. We also show the family has an additive $6 d_{\max}$ error for converting a fractional flow into an unsplittable one.
We study binary search for a target drawn from a distribution on $n$ ordered elements. The cost is the expected number of comparison queries. In our distributionally robust framework, the algorithm knows only an uncertainty set containing the distribution and minimizes its worst-case approximation ratio against an optimal strategy that knows the distribution. Collections of uncertainty sets capture different forms of information: quantiles, moments, general linear measurements, or approximate CDFs. This framework quantifies how much and what form of information is needed for near-optimal search. Our main result separates moments from general linear measurements. Although $n-1$ moments determine the distribution exactly, for every constant $\delta\in(0,1)$, the first $n^{1-\delta}$ exact moments can be as uninformative for search as no information: the worst-case approximation ratio remains $\Omega(\log n)$. In contrast, for every constant $\varepsilon\in(0,1)$, $O(n^\varepsilon\log^4 n)$ suitably chosen linear measurements suffice for an $O(1/\varepsilon)$-approximation. The limitation lies in the measurements chosen, rather than linearity itself. Using LP duality and polynomial bounds of Rakhmanov and Bernstein, we construct distributions with identical moments and mass concentrated at different positions. For the upper bound, we combine dyadic sketches and Johnson--Lindenstrauss embeddings with a truncated median-search algorithm that converts uniform CDF approximation into search guarantees. Measuring information in bits, we prove a lower bound of $\Omega(1/\varepsilon)$ on the approximation ratio for summaries of any form using at most $\frac12 n^\varepsilon\log n$ bits, for every sufficiently small constant $\varepsilon>0$. Quantiles match this within constant factors. For Kolmogorov balls of radius $n^{-\varepsilon}$ the optimal approximation ratio is $\Theta(1/\varepsilon)$.
We study the following family of search problems: given a system of equations $x+y+z\equiv 0\pmod p$ promised to admit a solution that is nonconstant on every equation, find a $c$-colouring of the variables that makes no equation monochromatic. For $p\in\{2,3\}$, the problem recovers known tractable Promise Constraint Satisfaction Problems (PCSPs). For $p > 3$, we obtain a complete complexity classification: the problem is polynomial-time solvable for $c \geq 4$, yet even its decision version is NP-hard for $c = 3$, and it is not well-defined for $c = 2$. Our main conceptual contribution is a general tractability framework for PCSPs based on Abelian embeddings, a notion introduced by Bhangale, Khot, and Minzer [STOC 2022] in the study of quantitative approximation of satisfiable CSPs. We show that suitable Abelian embeddings yield polynomial-time PCSP reductions realised by singleton algorithms in the sense of Zhuk [FOCS 2026]. On the hardness side, the promise relation is far removed from the reconfigurable regime covered by the conditional hardness framework of Banakh, Barsukov, and Nakajima [LICS 2026]; our proof instead relies on a new additive-combinatorial rigidity theorem classifying special $3$-colourings of $\mathbb{Z}_p$.
In the hat guessing game on a graph $G$, each vertex is occupied by a player wearing a hat whose color is chosen from a set of $q$ colors. Each player knows the graph and their position in it and sees only the hat colors of their neighbors. The players may agree on a strategy beforehand but must simultaneously try to guess their own hat colors without communicating. They win if at least one player guesses their own hat color correctly. The hat guessing number of $G$, denoted by $\textrm{HG}(G)$, is the largest integer $q$ for which the players have a strategy that guarantees a win for every assignment of hat colors. A direct application of the symmetric Lov\'asz Local Lemma shows that $\textrm{HG}(G) < e\Delta$ for every graph $G$ of maximum degree at most $\Delta \ge 1$. We prove that this bound is asymptotically sharp: for every $\varepsilon > 0$ and every sufficiently large $\Delta$, there exists a graph $G$ of maximum degree at most $\Delta$ with $\textrm{HG}(G) \ge (e - \varepsilon)\Delta$. This answers a question of Alon et al., disproves the conjecture $\textrm{HG}(G) \le 2\Delta(G)$ of Bosek et al., and improves on the construction of Latyshev and Kokhas, which achieves $\textrm{HG}(G) = 4\Delta(G)/3$. The hat guessing number thus provides a natural combinatorial problem in which the Lov\'asz Local Lemma is asymptotically tight.
We show that for every $\gamma>0$ and every sufficiently large $\Delta$, the Glauber dynamics for proper $q$-colorings of any $n$-vertex graph of maximum degree $\Delta$ has spectral gap $\Omega_\gamma(1/n)$, and hence mixing time $O_\gamma(n^2\log q)$, whenever $q\ge(1+1/\mathrm{e}+\gamma)\Delta$. Our proof establishes a Bochner-type inequality by exploiting the spectral gaps of hard-core models hidden in the color classes. The constant $1+1/\mathrm{e}\approx1.368$ comes from the uniqueness threshold $\approx\mathrm{e}/\Delta$ of the hard-core model on the infinite $\Delta$-regular tree.
A hypergraph $H = (V,E)$ describes a set system over a vertex universe $V$. Hypergraphs are increasingly popular in network science, as they represent interactions between subsets of vertices. A natural challenge is to design a data structure for $H$ to quickly answer basic questions about it, e.g. how many neighbors a vertex $v$ has or whether a hyperedge contains a vertex subset $S$. Such questions are trivial for graphs, for which we simply inspect the adjacency list. The gold standard, from a data structures perspective, would be near-linear time preprocessing and query answering in (poly)logarithmic time. Since this is unlikely for arbitrary $H$, we ask for well-motivated hypergraph properties that can make such a goal possible. We introduce bidegeneracy, a measure of hypergraph sparsity that strictly generalizes many other measures, including bounded degree, bounded rank, and bounded $\infty$-degeneracy. We show that bounded bidegeneracy yields fast hypergraph data structures. For a large set of fundamental queries, including their listing and sampling versions, we obtain near-linear preprocessing and (poly)logarithmic query time. Moreover, direct reductions from assumptions like the Orthogonal Vectors Conjecture suggest that, without assumptions on the input, these structures require almost-quadratic preprocessing or almost-linear query time. We use bidegeneracy to compute a compressed representation of $H$ and perform careful reductions to stabbing and searching problems in $\mathbb{R}^d$. Our framework significantly extends the well-studied "partial matching" problem of finding database entries through wildcard search. It also uncovers an intriguing connection between hypergraph sparsity, compression, and the complexity of hypergraph primitives. We also find remarkably low bidegeneracy in hypergraph datasets from the literature, suggesting practical consequences.
The Nash-Williams--Tutte theorem characterizes the existence of $k$ edge-disjoint spanning trees by a condition on every vertex partition. We prove that, for simple graphs, the same condition guarantees $k$ edge-disjoint spanning trees, each of diameter $O(n/\delta)$ and with $O((n/\delta)\log(\delta+1))$ internal vertices, where $n$ is the number of vertices and $\delta$ is the minimum degree. Both bounds hold simultaneously for every tree, with absolute implicit constants independent of $k$, and each is asymptotically optimal in general. Our proof is constructive and yields a randomized algorithm with expected running time $\tilde{O}(n^5)$. We derive applications to short edge-disjoint routes and weak linkages, small Steiner trees, and survivable networks with short paths. The joint bounds also yield low-diameter spanning Eulerian subgraphs and short tours for postman and general routing problems.
In classical gossiping, each participant initially knows a distinct piece of information. Whenever two participants call each other, they exchange everything they know. We study Gossiping: given an undirected multigraph whose vertices represent participants and whose edges represent available calls, decide whether the calls can be ordered so that every participant learns all information, using each edge at most once. Equivalently, can one time label per edge make the graph temporally connected by strict temporal paths? This recognition problem is NP-complete; we study its parameterized complexity. After linear-time preprocessing, we give an exact $O(3^{n/3}n^3)$-time algorithm and a deterministic $2^{O(tw)}n$-time algorithm, where $n$ is the number of vertices and $tw$ is the treewidth of the underlying simple graph. We introduce a Tree Contraction Rule that extends the treewidth algorithm to single-exponential algorithms for parameters that may remain small on dense graphs, such as tree-independence number and clique-width, without requiring a decomposition as input. For the excess $\delta=m-(2n-4)$ over the minimum number of calls, where $m$ is the number of edges, we give a randomized $2^{O(\delta)}n^3$-time algorithm with one-sided error. Its main subroutine solves Rooted Independent Cycle: finding a cycle through four prescribed vertices whose edges are independent in a represented linear matroid. We solve this problem deterministically in $2^{O(r)}m$ arithmetic operations over the finite field representing the matroid, where $r$ is its rank. Gossiping is polynomial-time solvable at maximum degree four, counting parallel edges, but NP-complete on planar simple graphs of maximum degree five. The treewidth algorithm yields a $2^{O(\sqrt n)}$-time algorithm on planar graphs.
Using the bisection bound of Monien and Preis, Fomin and H{\o}ie proved in 2006 that every graph of maximum degree 3 on $n$ vertices has pathwidth at most $n/6+o(n)$. We prove that the pathwidth, bisection width and cutwidth of these graphs are at most $c_3 n+o(n)$, where $c_3=\frac{3}{4\pi}\arccos\frac56\approx0.1398$. For bisection width this improves the bound $n/6+o(n)$ of Monien and Preis (2006) and extends to all such graphs the bound that Lichev and Mitsche (2023) obtained for random cubic graphs. For maximum degree 4, we prove that bisection width and cutwidth are at most $n/3+o(n)$, improving the bound $2n/5+o(n)$ of Monien and Preis for 4-regular graphs, and that pathwidth is at most $0.2458n$, improving the bound $n/3$ of Fomin, Gaspers, Saurabh and Stepanov (2009). We show that every graph with $m$ edges has pathwidth at most $7m/48+o(n)$, improving the bound $13m/75$ of Scott and Sorkin (2007), and we give further bounds of the form $\sum_{d\ge3}a_d n_d+o(n)$ with $a_d<1$, where $n_d$ is the number of vertices of degree $d$. The path decompositions, and linear orderings of the stated cutwidth, can be computed in polynomial time. Instead of deriving pathwidth bounds from bisection width, we give each vertex a Gaussian label, a weighted sum of independent standard normal variables over a ball around it, and sweep a threshold through the labels; the bags are frontiers, the vertices above the threshold with a neighbor below it. We bound the probability that a vertex lies in a frontier by comparison with an explicit Gaussian model of a vertex and its neighbors. Faster exact algorithms follow: for feedback vertex set and the traveling salesperson problem on graphs of bounded maximum or average degree, and on general graphs for minimum weight dominating set (by branching until the instance is sparse), Max 2-CSP and counting subgraphs with $k$ edges (by the bound in $m$).
The Weisfeiler-Leman algorithms WL(k) for $k\ge1$ form a hierarchy of increasingly powerful tests for graph isomorphism. We study how the equivalence relations they induce on graphs transfer through a graph operation $\Phi$: for a given $k$, what level of WL-equivalence between graphs $H_1$ and $H_2$ guarantees WL(k)-equivalence of graphs $\Phi(H_1)$ and $\Phi(H_2)$? We call the least such level the transfer parameter $\tau_\Phi(k)$ and determine it exactly for the line graph operation $\Phi = L$: $\tau_L(k)=2k+1$ for $k\ge2$, while $\tau_L(1)=1$. We also extend these results to the $(r,S)$-line graphs, which generalize the line graph from edges to $r$-cliques by connecting two cliques when their intersection size lies in a prescribed set $S$. For these operations we prove that $\tau_{r,S}(1)=r-1$ for every $S$ and, for certain choices of $S$, that $\tau_{r,S}(k)=rk+r-1$ for $k\ge r$, and we bound the transfer parameter in the remaining range. Our upper bounds on transfer parameters follow from a treewidth analysis of diagrammatic expansions of homomorphism counts into $\Phi(H)$ as linear combinations of homomorphism counts into $H$. The matching lower bounds combine explicit constructions of witness graphs with the homomorphism-distinguishing closedness of graphs of bounded treewidth.