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We exhibit an uncountable family of extremal inhomogeneous Gibbs measures of the low temperature Ising model on regular tilings of the hyperbolic plane. These states arise as low temperature perturbations of local ground states having a…

Probability · Mathematics 2025-07-25 Matteo D'Achille , Loren Coquille , Arnaud Le Ny

We present novel information-theoretic limits on detecting sparse changes in Ising models, a problem that arises in many applications where network changes can occur due to some external stimuli. We show that the sample complexity for…

Information Theory · Computer Science 2020-11-10 Aditya Gangrade , Bobak Nazer , Venkatesh Saligrama

The Ising spin glass is a one-parameter exponential family model for binary data with quadratic sufficient statistic. In this paper, we show that given a single realization from this model, the maximum pseudolikelihood estimate (MPLE) of…

Statistics Theory · Mathematics 2017-03-06 Bhaswar B. Bhattacharya , Sumit Mukherjee

Discrete Markov random fields form a natural class of models to represent images and spatial data sets. The use of such models is, however, hampered by a computationally intractable normalising constant. This makes parameter estimation and…

Computation · Statistics 2015-05-25 Haakon Michael Austad , Håkon Tjelmeland

We investigate the low-temperature critical behavior of the three dimensional random-field Ising ferromagnet. By a scaling analysis we find that in the limit of temperature $T \to 0$ the usual scaling relations have to be modified as far as…

Disordered Systems and Neural Networks · Physics 2015-06-25 U. Nowak , K. D. Usadel , J. Esser

This paper deals with the stochastic Ising model with a temperature shrinking to zero as time goes to infinity. A generalization of the Glauber dynamics is considered, on the basis of the existence of simultaneous flips of some spins. Such…

Probability · Mathematics 2017-01-20 Roy Cerqueti , Emilio De Santis

We consider the problem of estimating inverse temperature parameter $\beta$ of an $n$-dimensional truncated Ising model using a single sample. Given a graph $G = (V,E)$ with $n$ vertices, a truncated Ising model is a probability…

Machine Learning · Computer Science 2026-02-17 Rohan Chauhan , Ioannis Panageas

We consider a particular weak disorder limit ("continuum limit") of matrix products that arise in the analysis of disordered statistical mechanics systems, with a particular focus on random transfer matrices. The limit system is a diffusion…

Mathematical Physics · Physics 2020-06-08 Francis Comets , Giambattista Giacomin , Rafael L. Greenblatt

We consider the problem of estimating Ising models over $n$ variables in Total Variation (TV) distance, given $l$ independent samples from the model. While the statistical complexity of the problem is well-understood [DMR20], identifying…

Machine Learning · Computer Science 2025-11-27 Constantinos Daskalakis , Vardis Kandiros , Rui Yao

The ferromagnetic Ising model is a model of a magnetic material and a central topic in statistical physics. It also plays a starring role in the algorithmic study of approximate counting: approximating the partition function of the…

Data Structures and Algorithms · Computer Science 2021-11-05 Charlie Carlson , Ewan Davies , Alexandra Kolla , Will Perkins

The statistical mechanics of spin models, such as the Ising or Potts models, on generic random graphs can be formulated economically by considering the N --> 1 limit of Hermitian matrix models. In this paper we consider the N --> 1 limit in…

High Energy Physics - Lattice · Physics 2009-10-30 D. A. Johnston , P. Plechac

In this article, we study the large-population limit of interacting particle systems posed on weighted random graphs. In that aim, we introduce a general framework for the construction of weighted random graphs, generalizing the concept of…

Analysis of PDEs · Mathematics 2023-07-25 Nathalie Ayi , Nastassia Pouradier Duteil

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

In a recent paper [15], Giardin{\`a}, Giberti, Hofstad, Prioriello have proved a law of large number and a central limit theorem with respect to the annealed measure for the magnetization of the Ising model on some random graphs including…

Probability · Mathematics 2017-06-27 Van Hao Can

We study various mathematical aspects of discrete models on graphs, specifically the Dimer and the Ising models. We focus on proving gluing formulas for individual summands of the partition function. We also obtain partial results regarding…

Combinatorics · Mathematics 2011-10-30 Igor Kriz , Martin Loebl , Petr Somberg

We propose a covariate-dependent discrete graphical model for capturing dynamic networks among discrete random variables, allowing the dependence structure among vertices to vary with covariates. This discrete dynamic network encompasses…

Methodology · Statistics 2025-11-19 Lyndsay Roach , Qiong Li , Nanwei Wang , Xin Gao

This paper considers a non-standard problem of generating samples from a low-temperature Gibbs distribution with \emph{constrained} support, when some of the coordinates of the mode lie on the boundary. These coordinates are referred to as…

Statistics Theory · Mathematics 2026-02-27 Ruixiao Wang , Xiaohong Chen , Sinho Chewi

We study joint estimation of the inverse temperature and magnetization parameters $(\beta,B)$ of an Ising model with a non-negative coupling matrix $A_n$ of size $n\times n$, given one sample from the Ising model. We give a general bound on…

Statistics Theory · Mathematics 2018-01-23 Promit Ghosal , Sumit Mukherjee

We study the 2-dimensional Ising model at critical temperature on a simply connected subset $\Omega_{\delta}$ of the square grid $\delta\mathbb{Z}^{2}$. The scaling limit of the critical Ising model is conjectured to be described by…

Mathematical Physics · Physics 2018-11-26 Reza Gheissari , Clément Hongler , S. C. Park

A new methodology for model determination in decomposable graphical Gaussian models is developed. The Bayesian paradigm is used and, for each given graph, a hyper inverse Wishart prior distribution on the covariance matrix is considered.…

Computation · Statistics 2015-03-13 Sophie Donnet , Jean-Michel Marin