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The dynamics of an asymmetric kinetic Ising model is studied. Two schemes for improving the existing mean-field description are proposed. In the first scheme, we derive the formulas for instantaneous magnetization, equal-time correlation,…

Disordered Systems and Neural Networks · Physics 2014-05-23 Haiping Huang , Yoshiyuki Kabashima

Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique…

Disordered Systems and Neural Networks · Physics 2021-05-13 Miguel Aguilera , S. Amin Moosavi , Hideaki Shimazaki

We develop an elementary mean field approach for fully asymmetric kinetic Ising models, which can be applied to a single instance of the problem. In the case of the asymmetric SK model this method gives the exact values of the local…

Disordered Systems and Neural Networks · Physics 2015-05-27 M. Mezard , J. Sakellariou

We study a modified mean-field approximation for the Ising Model in arbitrary dimension. Instead of taking a "central" spin, or a small "drop" of fluctuating spins coupled to the effective field of their nearest neighbors as in the…

High Energy Physics - Lattice · Physics 2009-06-09 Cayetano Di Bartolo , Lorenzo Leal

Non-equilibrium systems lack an explicit characterisation of their steady state like the Boltzmann distribution for equilibrium systems. This has drastic consequences for the inference of parameters of a model when its dynamics lacks…

Statistical Mechanics · Physics 2016-11-15 Simon L. Dettmer , H. Chau Nguyen , Johannes Berg

Recent work on random field Ising model is described briefly emphasizing exact solutions of the model in simple cases and their relevance in understanding equilibrium and non-equilibrium properties of systems with quenched disorder.

Statistical Mechanics · Physics 2007-05-23 Prabodh Shukla

Mean field approximation is a popular method to study the behaviour of stochastic models composed of a large number of interacting objects. When the objects are asynchronous, the mean field approximation of a population model can be…

Performance · Computer Science 2018-07-24 Nicolas Gast , Diego Latella , Mieke Massink

We use an efficient method that eases the daunting task of simulating dynamics in spin systems with long-range interaction. Our Monte Carlo simulations of the long-range Ising model for the nonequilibrium phase ordering dynamics in two…

Statistical Mechanics · Physics 2019-01-23 Henrik Christiansen , Suman Majumder , Wolfhard Janke

The random field Ising model with Gaussian disorder is studied using a new Monte Carlo algorithm. The algorithm combines the advantanges of the replica exchange method and the two-replica cluster method and is much more efficient than the…

Statistical Mechanics · Physics 2009-10-31 Jon Machta , Mark Newman , Lincoln Chayes

A driven Ising model with friction due to magnetic correlations has recently been proposed by Kadau et al. (Phys. Rev. Lett. 101, 137205 (2008)). The non-equilibrium phase transition present in this system is investigated in detail using…

Statistical Mechanics · Physics 2010-01-05 Alfred Hucht

Detailed mean field and Monte Carlo studies of the dynamic magnetization-reversal transition in the Ising model in its ordered phase under a competing external magnetic field of finite duration have been presented here. Approximate…

Statistical Mechanics · Physics 2009-10-31 Arkajyoti Misra , Bikas K Chakrabarti

We investigate the quench dynamics of the transverse field Ising model on a finite fully connected lattice as a prime example of non-equilibrium mean field dynamics. Using a rate function approach we compute the leading order corrections to…

Statistical Mechanics · Physics 2019-10-24 Ingo Homrighausen , Stefan Kehrein

The inverse Ising problem consists in inferring the coupling constants of an Ising model given the correlation matrix. The fastest methods for solving this problem are based on mean-field approximations, but which one performs better in the…

Disordered Systems and Neural Networks · Physics 2012-08-28 Federico Ricci-Tersenghi

We study the stochastic parallel dynamics of Ising spin systems defined on finitely connected directed random graphs with arbitrary degree distributions, using generating functional analysis. For fully asymmetric graphs the dynamics of the…

Disordered Systems and Neural Networks · Physics 2009-09-24 Kazushi Mimura , A. C. C. Coolen

We extend previous mean-field approaches for non-equilibrium neural network models to estimate correlations in the system. This offers a powerful tool for approximating the system dynamics as well as a fast method to infer network…

Disordered Systems and Neural Networks · Physics 2022-01-27 Ángel Poc-López , Miguel Aguilera

This study proposes a novel approach based on the Ising model for analyzing socio-economic emerging patterns between municipalities by investigating the observed configuration of a network of selected territorial units which are classified…

Methodology · Statistics 2025-10-07 Pierpaolo Massoli

We present methods for approximating the mapping that defines the invariant manifold for two systems exhibiting generalized synchronization. If the equations of motion are known then an analytic approximation to the mapping can be found. If…

chao-dyn · Physics 2009-10-31 Reggie Brown

Non-equilibrium dynamics of classical random Ising spin chains are studied using asymptotically exact real space renormalization group. Specifically the random field Ising model with and without an applied field (and the Ising spin glass…

Condensed Matter · Physics 2009-10-31 Daniel S. Fisher , Pierre Le Doussal , Cecile Monthus

We propose a novel experimental protocol to measure generalized temporal entropies in many-body quantum systems. Our approach involves using local operators as probes to characterize the out-of-equilibrium dynamics induced by a geometric…

Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering ferromagnetism, combinatorial optimization, protein folding, stock market dynamics, and social dynamics.…

Disordered Systems and Neural Networks · Physics 2016-08-24 David Dahmen , Hannah Bos , Moritz Helias
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