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Markov Chain Monte Carlo (MCMC) underlies both statistical physics and combinatorial optimization, but mixes slowly near critical points and in rough landscapes. Parallel Tempering (PT) improves mixing by swapping replicas across…

Machine Learning · Computer Science 2025-09-30 Saleh Bunaiyan , Corentin Delacour , Shuvro Chowdhury , Kyle Lee , Kerem Y. Camsari

Recently, Velazquez and Curilef have proposed a methodology to extend Monte Carlo algorithms based on canonical ensemble, which is aimed to overcome slow sampling problems associated with temperature-driven discontinuous phase transitions.…

Statistical Mechanics · Physics 2013-07-31 L. Velazquez , J. C. Castro-Palacio

Using MCMC to sample from a target distribution, $\pi(x)$ on a $d$-dimensional state space can be a difficult and computationally expensive problem. Particularly when the target exhibits multimodality, then the traditional methods can fail…

Methodology · Statistics 2026-01-14 Nicholas G. Tawn , Gareth O. Roberts

A new algorithm for Monte Carlo calculation of the double exchange model is studied. The algorithm is commonly applicable to wide classes of strongly correlated electron systems which involve itinerant electrons coupled with…

Strongly Correlated Electrons · Physics 2009-11-07 Nobuo Furukawa , Yukitoshi Motome , Hisaho Nakata

Parallel tempering Monte Carlo has proven to be an efficient method in optimization and sampling applications. Having an optimized temperature set enhances the efficiency of the algorithm through more-frequent replica visits to the…

Computational Physics · Physics 2019-11-11 Ignacio Rozada , Maliheh Aramon , Jonathan Machta , Helmut G. Katzgraber

We present a detailed description of the idea and procedure for the newly proposed Monte Carlo algorithm of tuning the critical point automatically, which is called the probability-changing cluster (PCC) algorithm [Y. Tomita and Y. Okabe,…

Statistical Mechanics · Physics 2009-11-07 Yusuke Tomita , Yutaka Okabe

Decoupling approach presents a novel solution/alternative to the highly time-consuming fluid-thermal-structural simulation procedures when thermal effects and resultant displacements on machine tools are analyzed. Using high dimensional…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-31 Janine Glänzel , Andreas Naumann , Tharun Suresh Kumar

We introduce a new update scheme to systematically improve the efficiency of parallel tempering simulations. We show that by adapting the number of sweeps between replica exchanges to the canonical autocorrelation time, the average…

Statistical Mechanics · Physics 2008-09-26 Elmar Bittner , Andreas Nussbaumer , Wolfhard Janke

In this paper we develop a new general Bayesian methodology that simultaneously estimates parameters of interest and the marginal likelihood of the model. The proposed methodology builds on Simulated Tempering, which is a powerful algorithm…

Computation · Statistics 2019-06-03 Biljana Jonoska Stojkova , David A. Campbell

In this paper we propose a novel method to study critical systems numerically by a combined collective-mode algorithm and Renormalization Group on the lattice. This method is an improved version of MCRG in the sense that it has all the…

Statistical Mechanics · Physics 2009-12-03 G. Palma , D. Zambrano

We demonstrate that the invaded cluster algorithm, recently introduced by Machta et al, is a fast and reliable tool for determining the critical temperature and the magnetic critical exponent of periodic and aperiodic ferromagnetic Ising…

Statistical Mechanics · Physics 2009-10-31 Oliver Redner , Michael Baake

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

This paper presents two conceptually simple methods for parallelizing a Parallel Tempering Monte Carlo simulation in a distributed volunteer computing context, where computers belonging to the general public are used. The first method uses…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-03-31 Kamran Karimi , Neil G. Dickson , Firas Hamze

We present an adaptive multi-GPU Exchange Monte Carlo method designed for the simulation of the 3D Random Field Model. The algorithm design is based on a two-level parallelization scheme that allows the method to scale its performance in…

Computational Physics · Physics 2016-08-10 C. A. Navarro , Wei Huang , Youjin Deng

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

A modern graphics processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two dimensional Ising model [T. Preis et al., J. Comp.…

Computational Physics · Physics 2010-07-22 Benjamin Block , Peter Virnau , Tobias Preis

The heat capacity and isomer distributions of the 38 atom Lennard-Jones cluster have been calculated in the canonical ensemble using parallel tempering Monte Carlo methods. A distinct region of temperature is identified that corresponds to…

Chemical Physics · Physics 2009-11-06 J. P. Neirotti , F. Calvo , David L. Freeman , J. D. Doll

We study the thermodynamic properties of the three-dimensional Blume-Capel model on the simple cubic lattice by means of computer simulations. In particular, we implement a parallelized variant of the multicanonical approach and perform…

Statistical Mechanics · Physics 2015-03-19 Johannes Zierenberg , Nikolaos G. Fytas , Wolfhard Janke

We apply and test the recently proposed "extended scaling" scheme in an analysis of the magnetic susceptibility of Ising systems above the upper critical dimension. The data are obtained by Monte Carlo simulations using both the…

Statistical Mechanics · Physics 2009-11-13 Bertrand Berche , Christophe Chatelain , Chania Dhall , Ralph Kenna , Robert Low , Jean-Charles Walter

We report a novel Monte Carlo scheme that greatly enhances the power of parallel-tempering simulations. In this method, we boost the accumulation of statistical averages by including information about all potential parallel tempering trial…

Statistical Mechanics · Physics 2007-05-23 Ivan Coluzza Daan Frenkel