Searcharxiv⌕ Search

arXiv subjects

Thuy Duong Vuong

Publications and source records attributed to Thuy Duong Vuong.

4 recordsLinked to original sources

Spectral independence, coupling with the stationary distribution, and the spectral gap of the Glauber dynamics

We present a new lower bound on the spectral gap of the Glauber dynamics for the Gibbs distribution of a spectrally independent $q$-spin system on a graph $G = (V,E)$ with maximum degree $Δ$. Notably, for several interesting examples, our bound covers the entire regime of $Δ$ excluded by arguments based on coupling with the stationary distribution. As concrete applications, by combining our new lower bound with known spectral independence computations and known coupling arguments: (1) We show that for a triangle-free graph $G = (V,E)$ with maximum degree $Δ\geq 3$, the Glauber dynamics for the uniform distribution on proper $k$-colorings with $k \geq (1.763\dots + δ)Δ$ colors has spectral gap $\tildeΩ_δ(|V|^{-1})$. Previously, such a result was known either if the girth of $G$ is at least $5$ [Dyer et.~al, FOCS 2004], or under restrictions on $Δ$ [Chen et.~al, STOC 2021; Hayes-Vigoda, FOCS 2003]. (2) We show that for a regular graph $G = (V,E)$ with degree $Δ\geq 3$ and girth at least $6$, and for any $\varepsilon, δ> 0$, the partition function of the hardcore model with fugacity $λ\leq (1-δ)λ_{c}(Δ)$ may be approximated within a $(1+\varepsilon)$-multiplicative factor in time $\tilde{O}_δ(n^{2}\varepsilon^{-2})$. Previously, such a result was known if the girth is at least $7$ [Efthymiou et.~al, SICOMP 2019]. (3) We show for the binomial random graph $G(n,d/n)$ with $d = O(1)$, with high probability, an approximately uniformly random matching may be sampled in time $O_{d}(n^{2+o(1)})$. This improves the corresponding running time of $\tilde{O}_{d}(n^{3})$ due to [Jerrum-Sinclair, SICOMP 1989; Jerrum, 2003].

cs.DS↗

Log-Concave Polynomials IV: Approximate Exchange, Tight Mixing Times, and Near-Optimal Sampling of Forests

We prove tight mixing time bounds for natural random walks on bases of matroids, determinantal distributions, and more generally distributions associated with log-concave polynomials. For a matroid of rank $k$ on a ground set of $n$ elements, or more generally distributions associated with log-concave polynomials of homogeneous degree $k$ on $n$ variables, we show that the down-up random walk, started from an arbitrary point in the support, mixes in time $O(k\log k)$. Our bound has no dependence on $n$ or the starting point, unlike the previous analyses [ALOV19,CGM19], and is tight up to constant factors. The main new ingredient is a property we call approximate exchange, a generalization of well-studied exchange properties for matroids and valuated matroids, which may be of independent interest. In particular, given function $μ: {[n] \choose k} \to \mathbb{R}_{\geq 0},$ our approximate exchange property implies that a simple local search algorithm gives a $k^{O(k)}$-approximation of $\max_{S} μ(S)$ when $μ$ is generated by a log-concave polynomial, and that greedy gives the same approximation ratio when $μ$ is strongly Rayleigh. As an application, we show how to leverage down-up random walks to approximately sample random forests or random spanning trees in a graph with $n$ edges in time $O(n\log^2 n).$ The best known result for sampling random forest was a FPAUS with high polynomial runtime recently found by \cite{ALOV19, CGM19}. For spanning tree, we improve on the almost-linear time algorithm by [Sch18]. Our analysis works on weighted graphs too, and is the first to achieve nearly-linear running time for these problems.

cs.DS↗

Towards the sampling Lovász Local Lemma

Let $Φ= (V, \mathcal{C})$ be a constraint satisfaction problem on variables $v_1,\dots, v_n$ such that each constraint depends on at most $k$ variables and such that each variable assumes values in an alphabet of size at most $[q]$. Suppose that each constraint shares variables with at most $Δ$ constraints and that each constraint is violated with probability at most $p$ (under the product measure on its variables). We show that for $k, q = O(1)$, there is a deterministic, polynomial time algorithm to approximately count the number of satisfying assignments and a randomized, polynomial time algorithm to sample from approximately the uniform distribution on satisfying assignments, provided that \[C\cdot q^{3}\cdot k \cdot p \cdot Δ^{7} < 1, \quad \text{where }C \text{ is an absolute constant.}\] Previously, a result of this form was known essentially only in the special case when each constraint is violated by exactly one assignment to its variables. For the special case of $k$-CNF formulas, the term $Δ^{7}$ improves the previously best known $Δ^{60}$ for deterministic algorithms [Moitra, J.ACM, 2019] and $Δ^{13}$ for randomized algorithms [Feng et al., arXiv, 2020]. For the special case of properly $q$-coloring $k$-uniform hypergraphs, the term $Δ^{7}$ improves the previously best known $Δ^{14}$ for deterministic algorithms [Guo et al., SICOMP, 2019] and $Δ^{9}$ for randomized algorithms [Feng et al., arXiv, 2020].

cs.DS↗

Graph pattern detection: Hardness for all induced patterns and faster non-induced cycles

We consider the pattern detection problem in graphs: given a constant size pattern graph $H$ and a host graph $G$, determine whether $G$ contains a subgraph isomorphic to $H$. Our main results are: * We prove that if a pattern $H$ contains a $k$-clique subgraph, then detecting whether an $n$ node host graph contains a not necessarily induced copy of $H$ requires at least the time for detecting whether an $n$ node graph contains a $k$-clique. The previous result of this nature required that $H$ contains a $k$-clique which is disjoint from all other $k$-cliques of $H$. * We show that if the famous Hadwiger conjecture from graph theory is true, then detecting whether an $n$ node host graph contains a not necessarily induced copy of a pattern with chromatic number $t$ requires at least the time for detecting whether an $n$ node graph contains a $t$-clique. This implies that: (1) under Hadwiger's conjecture for every $k$-node pattern $H$, finding an induced copy of $H$ requires at least the time of $\sqrt k$-clique detection, and at least size $ω(n^{\sqrt{k}/4})$ for any constant depth circuit, and (2) unconditionally, detecting an induced copy of a random $G(k,p)$ pattern w.h.p. requires at least the time of $Θ(k/\log k)$-clique detection, and hence also at least size $n^{Ω(k/\log k)}$ for circuits of constant depth. * Finally, we consider the case when the pattern is a directed cycle on $k$ nodes, and we would like to detect whether a directed $m$-edge graph $G$ contains a $k$-Cycle as a not necessarily induced subgraph. We resolve a 14 year old conjecture of [Yuster-Zwick SODA'04] on the complexity of $k$-Cycle detection by giving a tight analysis of their $k$-Cycle algorithm. Our analysis improves the best bounds for $k$-Cycle detection in directed graphs, for all $k>5$.

cs.CC↗