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Recently a cluster Monte Carlo algorithm has been used very successfully in the two-dimensional Edwards-Anderson (EA) model. We show that this algorithm and a variant thereof can also be used successfully in models with a non-zero spin…

Disordered Systems and Neural Networks · Physics 2015-06-24 Thomas Jorg

In 1986, Swendsen and Wang proposed a replica Monte Carlo algorithm for spin glasses [Phys. Rev. Lett. 57 (1986) 2607]. Two important ingredients are present, (1) the use of a collection of systems (replicas) at different of temperatures,…

Statistical Mechanics · Physics 2009-11-10 Jian-Sheng Wang , Robert H. Swendsen

We present cluster Monte Carlo algorithms for the $XYZ$ quantum spin models. In the special case of $S=1/2$, the new algorithm can be viewed as a cluster algorithm for the 8-vertex model. As an example, we study the $S=1/2$ $XY$ model in…

Condensed Matter · Physics 2009-10-28 N. Kawashima

We describe a novel switching algorithm based on a ``reverse'' Monte Carlo method, in which the potential is stochastically modified before the system configuration is moved. This new algorithm facilitates a generalized formulation of…

Soft Condensed Matter · Physics 2009-11-13 C. H. Mak , Arun K. Sharma

A continuous-time projection quantum Monte Carlo algorithm is employed to simulate the ground state of a short-range quantum spin-glass model, namely, the two-dimensional Edwards-Anderson Hamiltonian with transverse field, featuring…

Disordered Systems and Neural Networks · Physics 2024-12-24 L. Brodoloni , S. Pilati

Suitable cluster definitions have allowed researchers to describe many ordering transitions in spin systems as geometric phenomena related to percolation. For spin glasses and some other systems with quenched disorder, however, such a…

Disordered Systems and Neural Networks · Physics 2023-05-04 Lambert Münster , Martin Weigel

We study the 3D Edwards-Anderson model with binary interactions by Monte Carlo simulations. Direct evidence of finite-size scaling is provided, and the universal finite-size scaling functions are determined. Using an iterative extrapolation…

Disordered Systems and Neural Networks · Physics 2007-05-23 Matteo Palassini , Sergio Caracciolo

In this paper we present a dynamical Monte Carlo algorithm which is applicable to systems satisfying a clustering condition: during the dynamical evolution the system is mostly trapped in deep local minima (as happens in glasses, pinning…

Condensed Matter · Physics 2009-10-22 Werner Krauth , Olivier Pluchery

We report the results of Monte Carlo simulations on several spin glass models at low temperatures. By using the parallel tempering (Exchange Monte Carlo) technique we are able to equilibrate down to low temperatures, for moderate sizes, and…

Disordered Systems and Neural Networks · Physics 2007-05-23 Helmut G. Katzgraber , Matteo Palassini , A. P. Young

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other…

Statistical Mechanics · Physics 2009-05-21 L. A. Fernandez , V. Martin-Mayor , P. Verrocchio

We review the background of the cluster algorithms in Monte Carlo simulation of statistical physics problems. One of the first such successful algorithm was developed by Swendsen and Wang eight years ago. In contrast to the local…

Condensed Matter · Physics 2007-05-23 Jian-Sheng Wang

We propose a new effective cluster algorithm of tuning the critical point automatically, which is an extended version of Swendsen-Wang algorithm. We change the probability of connecting spins of the same type, $p = 1 - e^{- J/ k_BT}$, in…

Statistical Mechanics · Physics 2009-10-31 Yusuke Tomita , Yutaka Okabe

Starting from a Cluster Variational Method, and inspired by the correctness of the paramagnetic Ansatz (at high temperatures in general, and at any temperature in the 2D Edwards-Anderson model) we propose a novel message passing algorithm…

Disordered Systems and Neural Networks · Physics 2011-12-26 Alejandro Lage-Castellanos , Roberto Mulet , Federico Ricci-Tersenghi , Tommaso Rizzo

Spin systems with frustration and disorder are notoriously difficult to study both analytically and numerically. While the simulation of ferromagnetic statistical mechanical models benefits greatly from cluster algorithms, these accelerated…

Disordered Systems and Neural Networks · Physics 2015-08-18 Zheng Zhu , Andrew J. Ochoa , Helmut G. Katzgraber

Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each…

Statistical Mechanics · Physics 2017-04-07 Emilio Flores-Sola , Martin Weigel , Ralph Kenna , Bertrand Berche

We study the three-dimensional Edwards-Anderson model with binary interactions by Monte Carlo simulations. Direct evidence of finite-size scaling is provided, and the universal finite-size scaling functions are determined. Monte Carlo data…

Disordered Systems and Neural Networks · Physics 2009-10-31 Matteo Palassini , Sergio Caracciolo

We discuss a new Monte Carlo algorithm for the simulation of complex fluids. This algorithm employs geometric operations to identify clusters of particles that can be moved in a rejection-free way. It is demonstrated that this geometric…

Statistical Mechanics · Physics 2015-06-25 Erik Luijten , Jiwen Liu

An approximate numerical approach to spin models is proposed, in which the original lattice is transformed into a tree. This method is applied to the Edwards-Anderson spin glass model in two and three dimensions. It captures the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Naoki Kawashima

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

We propose an efficient Monte Carlo algorithm for simulating a ``hardly-relaxing" system, in which many replicas with different temperatures are simultaneously simulated and a virtual process exchanging configurations of these replica is…

Condensed Matter · Physics 2009-10-28 Koji Hukushima , Koji Nemoto
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