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We apply extensive Monte Carlo simulations to study the probability distribution $P(m)$ of the order parameter $m$ for the simple cubic Ising model with periodic boundary condition at the transition point. Sampling is performed with the…

计算物理 · 物理学 2020-03-18 Jiahao Xu , Alan M. Ferrenberg , David P. Landau

We discuss different approaches for studying the influence of disorder in the three-dimensional Ising model. From the theoretical point of view, renormalisation group calculations provide quite accurate results. Experiments carried out on…

统计力学 · 物理学 2007-05-23 Bertrand Berche , Pierre-Emmanuel Berche , Christophe Chatelain , Wolfhard Janke

The sensitivity of the random field Ising model to small random perturbations of the quenched disorder is studied via exact ground states obtained with a maximum-flow algorithm. In one and two space dimensions we find a mild form of chaos,…

无序系统与神经网络 · 物理学 2009-10-31 M. Alava , H. Rieger

With the help of the replica exchange Monte Carlo method and the improved Monte Carlo renormalization-group scheme, we investigate over a wide area in the phase diagram of the Gaussian random field Ising model on the simple cubic lattice.…

无序系统与神经网络 · 物理学 2009-10-31 M. Itakura

We present an efficient Monte Carlo algorithm for the simulation of the two-dimensional Random Field Ising Model (RFIM). The method combines the event-driven, rejection-free character of the Bortz Kalos-Lebowitz (BKL) algorithm with Glauber…

统计力学 · 物理学 2026-03-19 Luca Cattaneo , Federico Ettori , Giovanni Cerri , Paolo Biscari , Ezio Puppin

We study the three-dimensional Ising model at the critical point in the fixed-magnetization ensemble, by means of the recently developed geometric cluster Monte Carlo algorithm. We define a magnetic-field-like quantity in terms of…

统计力学 · 物理学 2009-10-31 H. W. J. Blöte , J. R. Heringa , M. M. Tsypin

The random-field Ising model (RFIM), one of the basic models for quenched disorder, can be studied numerically with the help of efficient ground-state algorithms. In this study, we extend these algorithm by various methods in order to…

无序系统与神经网络 · 物理学 2015-05-13 M. Zumsande , A. K. Hartmann

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform…

统计力学 · 物理学 2015-06-19 Jean-Charles Walter , Gerard Barkema

We present results of large-scale Monte Carlo simulations for a three-dimensional Ising model with short range interactions and planar defects, i.e., disorder perfectly correlated in two dimensions. We show that the phase transition in this…

无序系统与神经网络 · 物理学 2009-11-10 Rastko Sknepnek , Thomas Vojta

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…

统计力学 · 物理学 2009-10-31 Arkajyoti Misra , Bikas K Chakrabarti

We discuss several algorithms for sampling from unnormalized probability distributions in statistical physics, but using the language of statistics and machine learning. We provide a self-contained introduction to some key ideas and…

统计计算 · 统计学 2025-05-05 Michael F. Faulkner , Samuel Livingstone

The Ising model is a simple statistical model for ferromagnetism. There are analytic solutions for low dimensions and very efficient Monte Carlo methods, such as cluster algorithms, for simulating this model in special cases. However most…

计算物理 · 物理学 2021-08-25 Johann Ostmeyer , Evan Berkowitz , Thomas Luu , Marcus Petschlies , Ferenc Pittler

Recent work has shown that probabilistic models based on pairwise interactions-in the simplest case, the Ising model-provide surprisingly accurate descriptions of experiments on real biological networks ranging from neurons to genes.…

定量方法 · 定量生物学 2007-12-18 Tamara Broderick , Miroslav Dudik , Gasper Tkacik , Robert E. Schapire , William Bialek

The critical behavior of the disordered ferromagnetic Ising model is studied numerically by the Monte Carlo method in a wide range of variation of concentration of nonmagnetic impurity atoms. The temperature dependences of correlation…

无序系统与神经网络 · 物理学 2007-09-11 V. Prudnikov , P. Prudnikov , A. Vakilov , A. Krinitsyn

The dynamics of a random (quenched) field Ising model (in two dimension) at zero temperature in the presence of an additional sinusoidally oscillating homogeneous (in space) magnetic field has been studied by Monte Carlo simulation using…

凝聚态物理 · 物理学 2015-06-25 Muktish Acharyya

Multi-dimensional density of states provides a useful description of complex frustrated systems. Recent advances in Monte Carlo methods enable efficient calculation of the density of states and related quantities, which renew the interest…

无序系统与神经网络 · 物理学 2009-11-10 Yukito Iba , Hisanao Takahashi

We study the equilibrium properties of an Ising model on a disordered random network where the disorder can be quenched or annealed. The network consists of four-fold coordinated sites connected via variable length one-dimensional chains.…

统计力学 · 物理学 2015-06-22 Abdul N. Malmi-Kakkada , Oriol T. Valls , Chandan Dasgupta

The Ising model in the presence of a random field is investigated within the mean field approximation based on Landau expansion. The random field is drawn from the trimodal probability distribution $P(h_{i})=p \delta(h_{i}-h_{0}) + q \delta…

统计力学 · 物理学 2013-04-26 I. A. Hadjiagapiou

We employ Monte Carlo simulations in order to study dynamics of the magnetization and domain growth processes in the random-field Ising models with uniform and Gaussian random field distributions of varying strengths. Domain sizes are…

统计力学 · 物理学 2023-07-19 S. Hrivňak , M. Žukovič

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…

统计力学 · 物理学 2026-03-30 Sara Oliver-Bonafoux , Raul Toral , Amitabha Chakrabarti
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