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Related papers: On Testing for Parameters in Ising Models

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The main goal of the paper is to prove central limit theorems for the magnetization rescaled by $\sqrt{N}$ for the Ising model on random graphs with $N$ vertices. Both random quenched and averaged quenched measures are considered. We work…

We have studied the anisotropic three-dimensional nearest-neighbor Ising model with competitive interactions in an uniform longitudinal magnetic field $H$. The model consists of ferromagnetic interaction $J_{x}(J_{z})$ in the $x(z)$…

Statistical Mechanics · Physics 2012-06-29 Octavio D. R. Salmon , Minos A. Neto , J. Roberto Viana , Igor T. Padilha , J. R. de Sousa

We develop a recently-proposed mapping of the two-dimensional Ising model with random exchange (RBIM), via the transfer matrix, to a network model for a disordered system of non-interacting fermions. The RBIM transforms in this way to a…

Disordered Systems and Neural Networks · Physics 2011-08-05 F. Merz , J. T. Chalker

The ferromagnetic XY model on sparse random graphs in a randomly oriented field is analyzed via the belief propagation algorithm. At variance with the fully connected case and with the random field Ising model on the same topology, we find…

Disordered Systems and Neural Networks · Physics 2021-04-27 Cosimo Lupo , Giorgio Parisi , Federico Ricci-Tersenghi

The Ising model on a $restricted$ scale-free network (SFN) has been studied employing Monte Carlo simulations. This network is described by a power-law degree distribution in the form $P(k)~k^{-\alpha}$, and is called restricted, because…

Statistical Mechanics · Physics 2023-05-24 R. A. Dumer , M. Godoy

We study phase transitions and thermodynamic properties in the two-dimensional antiferromagnetic Ising model with next-nearest-neighbor interaction on a Kagome lattice by Monte Carlo simulations. A histogram data analysis shows that a…

Statistical Mechanics · Physics 2018-10-02 Magomed A. Magomedov , Magomedsheikh K. Ramazanov , Akay K. Murtazaev

A modified version of a finite random field Ising ferromagnetic model in an external magnetic field at zero temperature is presented to describe group decision making. Fields may have a non-zero average. A postulate of minimum…

Disordered Systems and Neural Networks · Physics 2015-06-25 Serge Galam

The random field Ising model is studied numerically at both zero and positive temperature. Ground states are mapped out in a region of random and external field strength. Thermal states and thermodynamic properties are obtained for all…

Statistical Mechanics · Physics 2009-11-11 Yong Wu , Jon Machta

Using a combinatorial method, the partition functions for two-dimensional nearest neighbour Ising models have been derived for a square lattice of 16 sites in the presence of the magnetic field. A novel hierarchical method of enumeration of…

Statistical Mechanics · Physics 2022-05-24 Anshu Priya , M V Sangaranarayanan

We study the equilibrium and dynamic phase transition properties of two-dimensional Ising model on a decorated triangular lattice under the influence of a time-dependent magnetic field composed of a periodic square wave part plus a time…

Statistical Mechanics · Physics 2023-07-25 Yusuf Yüksel

There has been a lot of work fitting Ising models to multivariate binary data in order to understand the conditional dependency relationships between the variables. However, additional covariates are frequently recorded together with the…

Machine Learning · Statistics 2012-09-28 Jie Cheng , Elizaveta Levina , Pei Wang , Ji Zhu

An Ising antiferromagnet on a stacked triangular lattice in zero field is studied by Monte Carlo simulations, focusing on the character of the low-temperature phase and the effect of the relative strength of the exchange interaction in the…

Statistical Mechanics · Physics 2016-03-04 M. Žukovič , L. Mižišin , A. Bobák

We propose a novel approach to the inverse Ising problem which employs the recently introduced Density Consistency approximation (DC) to determine the model parameters (couplings and external fields) maximizing the likelihood of given…

Statistical Mechanics · Physics 2021-04-01 Alfredo Braunstein , Giovanni Catania , Luca Dall'Asta , Anna Paola Muntoni

The problem of structure estimation in graphical models with latent variables is considered. We characterize conditions for tractable graph estimation and develop efficient methods with provable guarantees. We consider models where the…

Machine Learning · Statistics 2013-04-23 Animashree Anandkumar , Ragupathyraj Valluvan

The Ising model is one of the simplest and most well-established concepts to simulate phase transformations in complex materials. However, its most central constant, the interaction strength J between two nearest neighbors, is hard to…

Statistical Mechanics · Physics 2023-11-20 Jacob Holder , Daniel Kazenwadel , Peter Nielaba , Peter Baum

The two-dimensional Ising model with nearest-neighbor ferromagnetic and long-range dipolar interactions exhibits a rich phase diagram. The presence of the dipolar interaction changes the ferromagnetic ground state expected for the pure…

Statistical Mechanics · Physics 2010-02-18 Leandro G. Rizzi , Nelson A. Alves

We test an optimised hopping parameter expansion on various Z_2 lattice scalar field models: the Ising model, a spin-one model and lambda (phi)^4. We do this by studying the critical indices for a variety of optimisation criteria, in a…

High Energy Physics - Phenomenology · Physics 2007-05-23 T. S. Evans , M. Ivin

We propose a new method to determine the unknown parameter associated to a self-consistent harmonic approximation. We check the validity of our technique in the context of the sine-Gordon model. As a non trivial application we consider the…

High Energy Physics - Theory · Physics 2016-08-16 Aníbal Iucci , Carlos M. Naón

We study the problem of testing, using only a single sample, between mean field distributions (like Curie-Weiss, Erd\H{o}s-R\'enyi) and structured Gibbs distributions (like Ising model on sparse graphs and Exponential Random Graphs). Our…

Statistics Theory · Mathematics 2018-05-24 Guy Bresler , Dheeraj Nagaraj

We consider the fundamental problem of learning the parameters of an undirected graphical model or Markov Random Field (MRF) in the setting where the edge weights are chosen at random. For Ising models, we show that a multiplicative-weight…

Machine Learning · Computer Science 2024-11-19 Gautam Chandrasekaran , Adam Klivans
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