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We present a highly optimized implementation of a Monte Carlo (MC) simulator for the three-dimensional Ising spin-glass model with bimodal disorder, i.e., the 3D Edwards-Anderson model running on CUDA enabled GPUs. Multi-GPU systems…

Disordered Systems and Neural Networks · Physics 2016-05-04 Matteo Lulli , Massimo Bernaschi , Giorgio Parisi

Self-averaging of singular thermodynamic quantities at criticality for randomly and thermally diluted three dimensional Ising systems has been studied by the Monte Carlo approach. Substantially improved self-averaging is obtained for…

Statistical Mechanics · Physics 2009-10-31 M. I. Marques , J. A. Gonzalo

We investigate two-dimensional Ising systems with multisping interactions of three- (m=3) and four-body terms (m=4). The application of a new type of finite-size algorithm of de Oliveira allow us to clearly distinguish a first-order…

Statistical Mechanics · Physics 2009-10-31 Ubiraci P. C. Neves , J. R. Drugowich de Felicio

With Monte Carlo methods, we investigate the universality class of the depinning transition in the two-dimensional Ising model with quenched random fields. Based on the short-time dynamic approach, we accurately determine the depinning…

Computational Physics · Physics 2012-03-01 X. P. Qin , B. Zheng , N. J. Zhou

We implement a two-stage approach of the Wang-Landau algorithm to investigate the critical properties of the 3D Ising model with quenched bond randomness. In particular, we consider the case where disorder couples to the nearest-neighbor…

Statistical Mechanics · Physics 2011-06-03 P. E. Theodorakis , N. G. Fytas

Equilibrium systems evolve according to Detailed Balance (DB). This principe guided development of the Monte-Carlo sampling techniques, of which Metropolis-Hastings (MH) algorithm is the famous representative. It is also known that DB is…

Statistical Mechanics · Physics 2015-07-15 Konstantin S. Turitsyn , Michael Chertkov , Marija Vucelja

The Metropolis-Hastings (MH) algorithm is one of the most widely used Markov Chain Monte Carlo schemes for generating samples from Bayesian posterior distributions. The algorithm is asymptotically exact, flexible and easy to implement.…

Methodology · Statistics 2026-03-10 Estevão Prado , Christopher Nemeth , Chris Sherlock

We present numerical simulations of the random field Ising model in three dimensions at zero temperature. The critical exponents are found to agree with previous results. We study the magnetic susceptibility by applying a small magnetic…

Disordered Systems and Neural Networks · Physics 2014-03-21 Marco Picco , Nicolas Sourlas

Dilute dipolar Ising magnets remain a notoriously hard problem to tackle both analytically and numerically because of long-ranged interactions between spins as well as rare region effects. We study a new type of anisotropic dilute dipolar…

Disordered Systems and Neural Networks · Physics 2019-08-28 Tushar Kanti Bose , Roderich Moessner , Arnab Sen

A Monte Carlo Renormalization Group algorithm is used on the Ising model to derive critical exponents and the critical temperature. The algorithm is based on a minimum relative entropy iteration developed previously to derive potentials…

Computational Physics · Physics 2007-05-23 John P. Donohue

Adaptive importance sampling (AIS) methods provide a useful alternative to Markov Chain Monte Carlo (MCMC) algorithms for performing inference of intractable distributions. Population Monte Carlo (PMC) algorithms constitute a family of AIS…

Methodology · Statistics 2023-12-13 Soumyasundar Pal , Antonios Valkanas , Mark Coates

The principle and the efficiency of the Monte Carlo transfer-matrix algorithm are discussed. Enhancements of this algorithm are illustrated by applications to several phase transitions in lattice spin models. We demonstrate how the…

Condensed Matter · Physics 2009-10-28 M. P. Nightingale , H. W. J. Bloete

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

Recently Baumann et al. [arXiv:0709.3228v1] studied the phase-ordering kinetics of the two-dimensional Ising model with uniform spatially quenched disorder by Monte-Carlo simulations. They found that the two-time response and correlation…

Statistical Mechanics · Physics 2009-11-13 Haye Hinrichsen

In this paper, we theoretically study the critical properties of the classical spin-1 Ising model using two approaches: 1) the analytical low-temperature series expansion and 2) the numerical Metropolis Monte Carlo technique. Within this…

Statistical Mechanics · Physics 2020-07-20 Amir Taheridehkordi , Roberto Zivieri

Extensive Monte Carlo simulations in the semi-grand-canonical ensemble are used to study the critical behavior of a three-dimensional compressible Ising model with antiferromagnetic interactions under constant volume conditions. Elastic…

Statistical Mechanics · Physics 2009-11-10 Luigi Cannavacciuolo , D. P. Landau

Monte Carlo simulation techniques, like simulated annealing and parallel tempering, are often used to evaluate low-temperature properties and find ground states of disordered systems. Here we compare these methods using direct calculations…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. J. Moreno , H. G. Katzgraber , Alexander K. Hartmann

The thinning method for numerical generation of the nonhomogeneous Poisson process (NHPP) arrival times has been adapted to accelerate Monte Carlo simulations of the kinetic Ising models (KIMs) with the Glauber spin-flip dynamics. The…

Statistical Mechanics · Physics 2025-06-02 V. I. Tokar , H. Dreyssé

While the 3d Ising model has defied analytic solution, various numerical methods like Monte Carlo, MCRG and series expansion have provided precise information about the phase transition. Using Monte Carlo simulation that employs the Wolff…

Computational Physics · Physics 2018-06-12 Alan M. Ferrenberg , Jiahao Xu , David P. Landau

The problem of optimally scaling the proposal distribution in a Markov chain Monte Carlo algorithm is critical to the quality of the generated samples. Much work has gone into obtaining such results for various Metropolis-Hastings (MH)…

Computation · Statistics 2022-02-07 Sanket Agrawal , Dootika Vats , Krzysztof Łatuszyński , Gareth O. Roberts