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This paper deals with the construction of a correlation decay tree (hypertree) for interacting systems modeled using graphs (hypergraphs) that can be used to compute the marginal probability of any vertex of interest. Local message passing…

Probability · Mathematics 2007-05-23 Chandra Nair , Prasad Tetali

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 show that the Glauber dynamics on proper 9-colourings of the triangular lattice is rapidly mixing, which allows for efficient sampling. Consequently, there is a fully polynomial randomised approximation scheme (FPRAS) for counting proper…

Mathematical Physics · Physics 2010-10-27 Markus Jalsenius

We present a unifying proof to derive the strong spatial mixing (SSM) property for the general 2-spin system from zero-free regions of its partition function. Our proof works for the multivariate partition function over all three complex…

Mathematical Physics · Physics 2025-02-11 Shuai Shao , Xiaowei Ye

We prove that the single-site Glauber dynamics for sampling proper $q$-colorings mixes in $O_\Delta(n\log n)$ time on line graphs with $n$ vertices and maximum degree $\Delta$ when $q>(1+o(1))\Delta$. The main tool in our proof is the…

Data Structures and Algorithms · Computer Science 2024-03-25 Yulin Wang , Chihao Zhang , Zihan Zhang

We introduce a new perfect sampling technique that can be applied to general Gibbs distributions and runs in linear time if the correlation decays faster than the neighborhood growth. In particular, in graphs with sub-exponential…

Data Structures and Algorithms · Computer Science 2020-04-27 Weiming Feng , Heng Guo , Yitong Yin

We present a simple algorithm that perfectly samples configurations from the unique Gibbs measure of a spin system on a potentially infinite graph $G$. The sampling algorithm assumes strong spatial mixing together with subexponential growth…

Data Structures and Algorithms · Computer Science 2021-07-01 Konrad Anand , Mark Jerrum

We consider correlation decay in the hard-core model with fugacity $\lambda$ on a rooted tree $T$ in which the arity of each vertex is independently Poisson distributed with mean $d$. Specifically, we investigate the question of which…

Probability · Mathematics 2015-02-24 Varsha Dani , Thomas P. Hayes , Cristopher Moore

In the context of stationary $\mathbb{Z}^d$ nearest-neighbour Gibbs measures $\mu$ satisfying strong spatial mixing, we present a new combinatorial condition (the topological strong spatial mixing property (TSSM)) on the support of $\mu$…

Dynamical Systems · Mathematics 2014-11-11 Raimundo Briceño

We consider spin systems with nearest-neighbor interactions on an $n$-vertex $d$-dimensional cube of the integer lattice graph $\mathbb{Z}^d$. We study the effects that exponential decay with distance of spin correlations, specifically the…

Discrete Mathematics · Computer Science 2017-08-07 Antonio Blanca , Pietro Caputo , Alistair Sinclair , Eric Vigoda

In the MSSM, we make a careful tree-level study of Charge and Color Breaking conditions in the plane $(H_2, \tilde{u}_L, \tilde{u}_R)$, focusing on the top quark scalar case. A simple and fast procedure to compute the VEVs of the dangerous…

High Energy Physics - Phenomenology · Physics 2011-01-13 C. Le Mouel

Given a countable graph $\mathcal{G}$ and a finite graph $\mathrm{H}$, we consider $\mathrm{Hom}(\mathcal{G},\mathrm{H})$ the set of graph homomorphisms from $\mathcal{G}$ to $\mathrm{H}$ and we study Gibbs measures supported on…

Combinatorics · Mathematics 2015-10-07 Raimundo Briceño , Ronnie Pavlov

We quantify the parameter stability of a spherical Gaussian Mixture Model (sGMM) under small perturbations in distribution space. Namely, we derive the first explicit bound to show that for a mixture of spherical Gaussian $P$ (sGMM) in a…

Machine Learning · Statistics 2023-02-02 Hanyu Zhang , Marina Meila

The Swendsen-Wang algorithm is a sophisticated, widely-used Markov chain for sampling from the Gibbs distribution for the ferromagnetic Ising and Potts models. This chain has proved difficult to analyze, due in part to the global nature of…

Probability · Mathematics 2021-05-11 Antonio Blanca , Zongchen Chen , Daniel Štefankovič , Eric Vigoda

We consider the problem of sampling a proper $k$-coloring of a graph of maximal degree $\Delta$ uniformly at random. We describe a new Markov chain for sampling colorings, and show that it mixes rapidly on graphs of bounded treewidth if…

Data Structures and Algorithms · Computer Science 2017-08-10 Shai Vardi

We address the convergence rate of Markov chains for randomly generating an edge coloring of a given tree. Our focus is on the Glauber dynamics which updates the color at a randomly chosen edge in each step. For a tree $T$ with $n$ vertices…

Discrete Mathematics · Computer Science 2024-07-08 Charlie Carlson , Xiaoyu Chen , Weiming Feng , Eric Vigoda

In a recent paper the last author proved that absence of complex zeros of the partition function of the hard-core model near a parameter $\lambda>0$ implies a form of correlation decay called strong spacial mixing. In this paper we…

Probability · Mathematics 2026-03-19 Han Peters , Josias Reppekus , Guus Regts

We address the problem of sampling colorings of a graph $G$ by Markov chain simulation. For most of the article we restrict attention to proper $q$-colorings of a path on $n$ vertices (in statistical physics terms, the one-dimensional…

Probability · Mathematics 2007-05-23 Martin Dyer , Leslie Ann Goldberg , Mark Jerrum

We provide an optimally mixing Markov chain for 6-colorings of the square lattice on rectangular regions with free, fixed, or toroidal boundary conditions. This implies that the uniform distribution on the set of such colorings has strong…

Statistical Mechanics · Physics 2015-06-25 Dimitris Achlioptas , Michael Molloy , Cristopher Moore , Frank Van Bussell

Spatial-sign covariance matrix (SSCM) is an important substitute of sample covariance matrix (SCM) in robust statistics. This paper investigates the SSCM on its asymptotic spectral behaviors under high-dimensional elliptical populations,…

Statistics Theory · Mathematics 2017-05-19 Weiming Li , Wang Zhou