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The maximum independent set (MIS) problem is a well-studied combinatorial optimization problem that naturally arises in many applications, such as wireless communication, information theory and statistical mechanics. MIS problem is NP-hard,…

Discrete Mathematics · Computer Science 2015-04-20 Rémi Varloot , Ana Bušić , Anne Bouillard

We give the first comprehensive analysis of the effect of boundary conditions on the mixing time of the Glauber dynamics in the so-called Bethe approximation. Specifically, we show that spectral gap and the log-Sobolev constant of the…

Probability · Mathematics 2009-11-10 Fabio Martinelli , Alistair Sinclair , Dror Weitz

We consider spin systems on general $n$-vertex graphs of unbounded degree and explore the effects of spectral independence on the rate of convergence to equilibrium of global Markov chains. Spectral independence is a novel way of…

Probability · Mathematics 2023-08-30 Antonio Blanca , Xusheng Zhang

We prove that Ising models on the hypercube with general quadratic interactions satisfy a Poincar\'{e} inequality with respect to the natural Dirichlet form corresponding to Glauber dynamics, as soon as the operator norm of the interaction…

Probability · Mathematics 2021-08-10 Ronen Eldan , Frederic Koehler , Ofer Zeitouni

For general spin systems, we prove that a contractive coupling for any local Markov chain implies optimal bounds on the mixing time and the modified log-Sobolev constant for a large class of Markov chains including the Glauber dynamics,…

We study the stochastic Ising model on finite graphs with n vertices and bounded degree and analyze the effect of boundary conditions on the mixing time. We show that for all low enough temperatures, the spectral gap of the dynamics with…

Probability · Mathematics 2008-11-10 Alessandra Bianchi

We study the hard-core model defined on independent sets, where each independent set I in a graph G is weighted proportionally to $\lambda^{|I|}$, for a positive real parameter $\lambda$. For large $\lambda$, computing the partition…

Probability · Mathematics 2011-08-15 Ricardo Restrepo , Jinwoo Shin , Prasad Tetali , Eric Vigoda , Linji Yang

Motivated by the `subgraphs world' view of the ferromagnetic Ising model, we develop a general approach to studying mixing times of Glauber dynamics based on subset expansion expressions for a class of graph polynomials. With a canonical…

Combinatorics · Mathematics 2015-10-29 Magnus Bordewich , Ross J. Kang

We present a simple combinatorial framework for establishing approximate tensorization of variance and entropy in the setting of spin systems (a.k.a. undirected graphical models) based on balanced separators of the underlying graph. Such…

Data Structures and Algorithms · Computer Science 2023-07-18 Zongchen Chen

Recently, Eldan, Koehler, and Zeitouni (2020) showed that Glauber dynamics mixes rapidly for general Ising models so long as the difference between the largest and smallest eigenvalues of the coupling matrix is at most $1 - \epsilon$ for…

Data Structures and Algorithms · Computer Science 2023-12-01 Dmitriy Kunisky

We study continuous time Glauber dynamics for random configurations with local constraints (e.g. proper coloring, Ising and Potts models) on finite graphs with $n$ vertices and of bounded degree. We show that the relaxation time (defined as…

Probability · Mathematics 2016-09-07 Noam Berger , Claire Kenyon , Elchanan Mossel , Yuval Peres

This paper formalizes connections between stability of polynomials and convergence rates of Markov Chain Monte Carlo (MCMC) algorithms. We prove that if a (multivariate) partition function is nonzero in a region around a real point…

Data Structures and Algorithms · Computer Science 2024-08-07 Zongchen Chen , Kuikui Liu , Eric Vigoda

We consider the problem of sampling from the Ising model when the underlying interaction matrix has eigenvalues lying within an interval of length $\gamma$. Recent work in this setting has shown various algorithmic results that apply…

Data Structures and Algorithms · Computer Science 2024-07-11 Andreas Galanis , Alkis Kalavasis , Anthimos Vardis Kandiros

For distributions over discrete product spaces $\prod_{i=1}^n \Omega_i'$, Glauber dynamics is a Markov chain that at each step, resamples a random coordinate conditioned on the other coordinates. We show that $k$-Glauber dynamics, which…

Data Structures and Algorithms · Computer Science 2024-07-11 Holden Lee

Motivated by the community detection problem in Bayesian inference, as well as the recent explosion of interest in spin glasses from statistical physics, we study the classical Glauber dynamics for sampling from Ising models with sparse…

Probability · Mathematics 2024-08-07 Kuikui Liu , Sidhanth Mohanty , Amit Rajaraman , David X. Wu

We prove that the the mixing time of the Glauber dynamics for sampling independent sets on $n$-vertex $k$-uniform hypergraphs is $O(n\log n)$ when the maximum degree $\Delta$ satisfies $\Delta \leq c 2^{k/2}$, improving on the previous…

Probability · Mathematics 2019-12-25 Jonathan Hermon , Allan Sly , Yumeng Zhang

The hard core model in statistical physics is a probability distribution on independent sets in a graph in which the weight of any independent set I is proportional to lambda^(|I|), where lambda > 0 is the vertex activity. We show that…

Discrete Mathematics · Computer Science 2016-11-17 Alistair Sinclair , Piyush Srivastava , Yitong Yin

We prove two results on the mixing times of Markov chains for two-spin systems. First, we show that the Glauber dynamics mixes in polynomial time for the Gibbs distributions of antiferromagnetic two-spin systems at the critical threshold of…

Data Structures and Algorithms · Computer Science 2026-05-04 Xiaoyu Chen , Zhe Ju , Tianshun Miao , Yitong Yin , Xinyuan Zhang

We study the worst-case mixing time of the global Kawasaki dynamics for the fixed-magnetization Ising model on the class of graphs of maximum degree $\Delta$. Proving a conjecture of Carlson, Davies, Kolla, and Perkins, we show that below…

Data Structures and Algorithms · Computer Science 2025-11-25 Aiya Kuchukova , Marcus Pappik , Will Perkins , Corrine Yap

We consider the problem of estimating the marginal independence structure of a Bayesian network from observational data, learning an undirected graph we call the unconditional dependence graph. We show that unconditional dependence graphs…

Methodology · Statistics 2024-05-22 Danai Deligeorgaki , Alex Markham , Pratik Misra , Liam Solus