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Related papers: On Testing for Parameters in Ising Models

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There is proposed a model of scale-free random graphs which are locally close to the uncorrelated complex random networks with divergent $\langle k^2 \rangle$ studied in e.g. S. N. Dorogovtsev {\it et al}, Rev. Mod. Phys. {\bf 80}, 1275…

Mathematical Physics · Physics 2011-09-22 Yuri Kozitsky

We present a new approach to a classical problem in statistical physics: estimating the partition function and other thermodynamic quantities of the ferromagnetic Ising model. Markov chain Monte Carlo methods for this problem have been…

Statistical Mechanics · Physics 2013-06-20 Amanda Streib , Noah Streib , Isabel Beichl , Francis Sullivan

Three dimensional Ising model ferromagnets on different lattices with nearest neighbor interactions, and on simple cubic lattices with equivalent interactions out to further neighbors, are studied numerically. The susceptibility data for…

Statistical Mechanics · Physics 2011-07-28 P. H. Lundow , I. A. Campbell

A periodic Ising model is one endowed with interactions that are invariant under translations of members of a full-rank sublattice $\mathfrak{L}$ of $\mathbb{Z}^2$. We give an exact, quantitative description of the critical temperature,…

Mathematical Physics · Physics 2012-04-10 Zhongyang Li

Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the…

Machine Learning · Computer Science 2019-07-09 Frank Nussbaum , Joachim Giesen

We study ferromagnetic Ising models on finite graphs with an inhomogeneous external field, where a subset of vertices is designated as the boundary. We show that the influence of boundary conditions on any given spin is maximised when the…

Probability · Mathematics 2022-03-29 Jian Ding , Jian Song , Rongfeng Sun

The partition functions for two-dimensional nearest neighbour Ising model in a non-zero magnetic field have been derived for finite square lattices with the help of graph theoretical procedures, show-bit algorithm, enumeration of…

Statistical Mechanics · Physics 2010-06-03 G. Nandhini , M. Vinoth Kumar , M. V. Sangaranarayanan

We study the Ising model under a time-varying, but spatially homogeneous, Gaussian random magnetic field. In the Monte Carlo simulations, we go beyond the standard analysis of the order parameter by measuring the magnetization probability…

Statistical Mechanics · Physics 2026-03-30 Sara Oliver-Bonafoux , Raul Toral , Amitabha Chakrabarti

We consider ferromagnetic Ising models on graphs that converge locally to trees. Examples include random regular graphs with bounded degree and uniformly random graphs with bounded average degree. We prove that the "cavity" prediction for…

Probability · Mathematics 2016-09-08 Amir Dembo , Andrea Montanari

The mean field approximation to the Ising model is a canonical variational tool that is used for analysis and inference in Ising models. We provide a simple and optimal bound for the KL error of the mean field approximation for Ising models…

Machine Learning · Computer Science 2018-02-22 Vishesh Jain , Frederic Koehler , Elchanan Mossel

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 the two-dimensional random field Ising model (RFIM) with bimodal (i.e., two-valued) external field, we prove exponential decay of correlations either (1) when the temperature is larger than the critical temperature of the Ising model…

Probability · Mathematics 2018-09-26 Federico Camia , Jianping Jiang , Charles M. Newman

There have been two separate lines of work on estimating Ising models: (1) estimating them from multiple independent samples under minimal assumptions about the model's interaction matrix; and (2) estimating them from one sample in…

Statistics Theory · Mathematics 2020-12-11 Yuval Dagan , Constantinos Daskalakis , Nishanth Dikkala , Anthimos Vardis Kandiros

We propose two different macroscopic dynamics to describe the decay of metastable phases in many-particle systems with local interactions. These dynamics depend on the macroscopic order parameter $m$ through the restricted free energy…

Condensed Matter · Physics 2016-08-31 J. Lee , M. A. Novotny , P. A. Rikvold

In this paper, we study the detection boundary for minimax hypothesis testing in the context of high-dimensional, sparse binary regression models. Motivated by genetic sequencing association studies for rare variant effects, we investigate…

Statistics Theory · Mathematics 2015-03-06 Rajarshi Mukherjee , Natesh S. Pillai , Xihong Lin

In this paper, we study the effect of dependence on detecting a class of signals in Ising models, where the signals are present in a structured way. Examples include Ising Models on lattices, and Mean-Field type Ising Models…

Probability · Mathematics 2020-12-11 Nabarun Deb , Rajarshi Mukherjee , Sumit Mukherjee , Ming Yuan

We study the problem of approximating the partition function of the ferromagnetic Ising model in graphs and hypergraphs. Our first result is a deterministic approximation scheme (an FPTAS) for the partition function in bounded degree graphs…

Data Structures and Algorithms · Computer Science 2018-12-26 Jingcheng Liu , Alistair Sinclair , Piyush Srivastava

We study the phase diagram and critical properties of quantum Ising chains with long-range ferromagnetic interactions decaying in a power-law fashion with exponent $\alpha$, in regimes of direct interest for current trapped ion experiments.…

Statistical Mechanics · Physics 2021-10-13 E. Gonzalez-Lazo , M. Heyl , M. Dalmonte , A. Angelone

We investigate the Ising model on a spherical surface, utilizing a Fibonacci lattice to approximate uniform coverage. This setup poses challenges in achieving consistent lattice distribution across the sphere for comparison with planar…

Computational Physics · Physics 2025-12-09 Zheng Zhou , Chen-Hui Song , Xu-Yang Hou , Hao Guo

As powerful as machine learning (ML) techniques are in solving problems involving data with large dimensionality, explaining the results from the fitted parameters remains a challenging task of utmost importance, especially in physics…

Disordered Systems and Neural Networks · Physics 2024-04-15 Roberto C. Alamino