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We prove an optimal mixing time bound on the single-site update Markov chain known as the Glauber dynamics or Gibbs sampling in a variety of settings. Our work presents an improved version of the spectral independence approach of Anari et…

Discrete Mathematics · Computer Science 2023-03-24 Zongchen Chen , Kuikui Liu , Eric Vigoda

An important paradigm in the understanding of mixing times of Glauber dynamics for spin systems is the correspondence between spatial mixing properties of the models and bounds on the mixing time of the dynamics. This includes, in…

Probability · Mathematics 2023-10-05 Reza Gheissari , Alistair Sinclair

We study the Potts model on locally tree-like random graphs of arbitrary degree distribution. Using a population dynamics algorithm we numerically solve the problem exactly. We confirm our results with simulations. Comparisons with a…

Statistical Mechanics · Physics 2009-11-10 G. C. M. A. Ehrhardt , M. Marsili

Given a graph $G$, the hard-core model defines a probability distribution over its independent sets, assigning to each set of size $k$ a probability of $\frac{\lambda^k}{Z}$, where $\lambda>0$ is a parameter known as the \emph{fugacity} and…

Data Structures and Algorithms · Computer Science 2025-11-24 Malory Marin

The Glauber dynamics on the colourings of a graph is a random process which consists in recolouring at each step a random vertex of a graph with a new colour chosen uniformly at random among the colours not already present in its…

Combinatorics · Mathematics 2020-11-04 Marc Heinrich

We study the sampling problem for the ferromagnetic Ising model with consistent external fields, and in particular, Swendsen-Wang dynamics on this model. We introduce a new grand model unifying two closely related models: the subgraph world…

Data Structures and Algorithms · Computer Science 2022-07-19 Weiming Feng , Heng Guo , Jiaheng Wang

We present an improved coupling technique for analyzing the mixing time of Markov chains. Using our technique, we simplify and extend previous results for sampling colorings and independent sets. Our approach uses properties of the…

Probability · Mathematics 2007-05-23 Thomas P. Hayes , Eric Vigoda

We consider the problem of generating uniformly random partitions of the vertex set of a graph such that every piece induces a connected subgraph. For the case where we want to have partitions with linearly many pieces of bounded size, we…

Probability · Mathematics 2022-06-02 Alan Frieze , Wesley Pegden

We study random walks on dynamically evolving graphs, where the environment is given by a time-dependent subset of the edges of an underlying graph. Concretely, following the recently introduced framework of Lelli and Stauffer, we consider…

Probability · Mathematics 2026-05-08 Andreas Galanis , Leslie Ann Goldberg , Xandru Mifsud

We show that the Potts model on a graph can be approximated by a sequence of independent and identically distributed spins in terms of Wasserstein distance at high temperatures. We prove a similar result for the Curie--Weiss--Potts model on…

Probability · Mathematics 2026-01-14 Roxanne He , Jackie Lok

We study the $q$-state ferromagnetic Potts model on the $n$-vertex complete graph known as the mean-field (Curie-Weiss) model. We analyze the Swendsen-Wang algorithm which is a Markov chain that utilizes the random cluster representation…

Discrete Mathematics · Computer Science 2017-11-27 Andreas Galanis , Daniel Stefankovic , Eric Vigoda

The exponential random graph model (ERGM) is a central object in the study of clustering properties in social networks as well as canonical ensembles in statistical physics. Despite some breakthrough works in the mathematical understanding…

Probability · Mathematics 2021-08-06 Shirshendu Ganguly , Kyeongsik Nam

Sampling graph colorings via local Markov chains is a central problem in approximate counting and Markov chain Monte Carlo (MCMC). We address the problem of sampling a random $k$-coloring of a graph with maximum degree $\Delta$. The…

Data Structures and Algorithms · Computer Science 2026-04-15 Vishesh Jain , Clayton Mizgerd , Eric Vigoda

We study the single-site Glauber dynamics for the fugacity $\lambda$, Hard-core model on the random graph $G(n, d/n)$. We show that for the typical instances of the random graph $G(n,d/n)$ and for fugacity $\lambda <…

Discrete Mathematics · Computer Science 2023-02-14 Charilaos Efthymiou , Weiming Feng

We give an FPTAS and an efficient sampling algorithm for the high-fugacity hard-core model on bounded-degree bipartite expander graphs and the low-temperature ferromagnetic Potts model on bounded-degree expander graphs. The results apply,…

Data Structures and Algorithms · Computer Science 2020-03-25 Matthew Jenssen , Peter Keevash , Will Perkins

We give a near-linear time sampler for the Gibbs distribution of the ferromagnetic Ising models with edge activities $\boldsymbol{\beta} > 1$ and external fields $\boldsymbol{\lambda}<1$ (or symmetrically, $\boldsymbol{\lambda}>1$) on…

Probability · Mathematics 2023-08-21 Xiaoyu Chen , Xinyuan Zhang

We study Markov chains for randomly sampling $k$-colorings of a graph with maximum degree $\Delta$. Our main result is a polynomial upper bound on the mixing time of the single-site update chain known as the Glauber dynamics for planar…

Probability · Mathematics 2011-09-01 Thomas P. Hayes , Juan C. Vera , Eric Vigoda

The antiferromagnetic Ising model samples subsets of vertices of a graph with weight decaying exponentially in the number of edges induced. We study the problem of sampling from this model on the class of bipartite, regular graphs with good…

Combinatorics · Mathematics 2026-03-03 Anna Geisler , Mihyun Kang , Michail Sarantis , Ronen Wdowinski

We study the mixing time of the single-site update Markov chain, known as the Glauber dynamics, for generating a random independent set of a tree. Our focus is obtaining optimal convergence results for arbitrary trees. We consider the more…

Discrete Mathematics · Computer Science 2025-03-05 Charilaos Efthymiou , Thomas P. Hayes , Daniel Stefankovic , Eric Vigoda

The hard-core model has as its configurations the independent sets of some graph instance $G$. The probability distribution on independent sets is controlled by a `fugacity' $\lambda>0$, with higher $\lambda$ leading to denser…

Probability · Mathematics 2026-01-14 Mark Jerrum