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Learning properties of large graphs from samples has been an important problem in statistical network analysis since the early work of Goodman \cite{Goodman1949} and Frank \cite{Frank1978}. We revisit a problem formulated by Frank…

Statistics Theory · Mathematics 2019-06-18 Jason M. Klusowski , Yihong Wu

Propp and Wilson's method of coupling from the past allows one to efficiently generate exact samples from attractive statistical distributions (e.g., the ferromagnetic Ising model). This method may be generalized to non-attractive…

Statistical Mechanics · Physics 2007-05-23 Andrew M. Childs , Ryan B. Patterson , David J. C. MacKay

We examine the problem of almost-uniform sampling proper $q$-colorings of a graph whose maximum degree is $\Delta$. A famous result, discovered independently by Jerrum(1995) and Salas and Sokal(1997), is that, assuming $q > (2+\delta)…

Data Structures and Algorithms · Computer Science 2018-06-22 Weiming Feng , Thomas P. Hayes , Yitong Yin

The importance-sampling Monte Carlo algorithm appears to be the universally optimal solution to the problem of sampling the state space of statistical mechanical systems according to the relative importance of configurations for the…

Statistical Mechanics · Physics 2010-06-22 Martin Weigel

We give tight upper and lower bounds on the internal energy per particle in the antiferromagnetic $q$-state Potts model on $4$-regular graphs, for $q\ge 5$. This proves the first case of a conjecture of the author, Perkins, Jenssen, and…

Combinatorics · Mathematics 2021-03-05 Ewan Davies

In this paper, we study estimation of parameters in a two-parameter Potts model with $q$ colors and coupling matrix $A_N$. We characterize concrete sufficient conditions for existence of the pseudo-likelihood estimator of the Potts model,…

Statistics Theory · Mathematics 2026-04-07 Somabha Mukherjee , Sumit Mukherjee , Sayar Karmakar

We develop an efficient algorithmic approach for approximate counting and sampling in the low-temperature regime of a broad class of statistical physics models on finite subsets of the lattice $\mathbb Z^d$ and on the torus $(\mathbb Z/n…

Data Structures and Algorithms · Computer Science 2023-06-19 Tyler Helmuth , Will Perkins , Guus Regts

The class of random-cluster models is a unification of a variety of stochastic processes of significance for probability and statistical physics, including percolation, Ising, and Potts models; in addition, their study has impact on the…

Probability · Mathematics 2007-05-23 Geoffrey Grimmett

We show that the mixing time of Glauber (single edge update) dynamics for the random cluster model at $q=2$ is bounded by a polynomial in the size of the underlying graph. As a consequence, the Swendsen-Wang algorithm for the ferromagnetic…

Data Structures and Algorithms · Computer Science 2016-05-03 Heng Guo , Mark Jerrum

We consider the $q$-state Potts model on families of self-dual strip graphs $G_D$ of the square lattice of width $L_y$ and arbitrarily great length $L_x$, with periodic longitudinal boundary conditions. The general partition function $Z$…

Statistical Mechanics · Physics 2009-11-07 Shu-Chiuan Chang , Robert Shrock

Fixing $\beta \ge 0$ and an integer $q \ge 2$, consider the ferromagnetic $q$-Potts measures $\mu_n^{\beta,B}$ on finite graphs ${\sf G}_n$ on $n$ vertices, with external field strength $B \ge 0$ and the corresponding random cluster…

Probability · Mathematics 2025-05-22 Anirban Basak , Amir Dembo , Allan Sly

A hierarchical froth model of the interface of a random $q$-state Potts ferromagnet in $2D$ is studied by recursive methods. A fraction $p$ of the nearest neighbour bonds is made inaccessible to domain walls by infinitely strong…

Condensed Matter · Physics 2009-10-28 Giovanni Sartoni , Attilio L. Stella

The q-state Potts model on a diamond chain has mathematical significance in analyzing phase transitions and critical behaviors in diverse fields, including statistical physics, condensed matter physics, and materials science. By focusing on…

Statistical Mechanics · Physics 2023-10-30 Yury Panov , Onofre Rojas

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

Exponential random graph models have become increasingly important in the study of modern networks ranging from social networks, economic networks, to biological networks. They seek to capture a wide variety of common network tendencies…

Probability · Mathematics 2019-06-07 Ryan DeMuse , Terry Easlick , Mei Yin

The hardcore model is a fundamental probabilistic model extensively studied in statistical physics, probability theory, and computer science. For graphs of maximum degree $\Delta$, a well-known computational phase transition occurs at the…

Data Structures and Algorithms · Computer Science 2025-11-13 Xiaoyu Chen , Zejia Chen , Zongchen Chen , Yitong Yin , Xinyuan Zhang

We consider the ferromagnetic q-state Potts model on a finite grid graph with non-zero external field and periodic boundary conditions. The system evolves according to Glauber-type dynamics described by the Metropolis algorithm, and we…

Probability · Mathematics 2024-05-09 Gianmarco Bet , Anna Gallo , Francesca R. Nardi

This article studies the planar Potts model and its random-cluster representation. We show that the phase transition of the nearest-neighbor ferromagnetic $q$-state Potts model on $\mathbb Z^2$ is continuous for $q\in\{2,3,4\}$, in the…

Probability · Mathematics 2016-11-03 Hugo Duminil-Copin , Vladas Sidoravicius , Vincent Tassion

We prove an inequality on decision trees on monotonic measures which generalizes the OSSS inequality on product spaces. As an application, we use this inequality to prove a number of new results on lattice spin models and their…

Probability · Mathematics 2018-12-27 Hugo Duminil-Copin , Aran Raoufi , Vincent Tassion

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