descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Other literature type 16 Dec 2015Embargo end date: 01 Jan 2015 English Publisher:American Physical Society (APS)Journal:Physical Review E, volume 92 (issn: 1539-3755, eissn: 1550-2376,

Authors: Wenlong Wang; Helmut G. Katzgraber; Jonathan Machta; Jonathan Machta;

doi: 10.1103/physreve.92.063307 , 10.48550/arxiv.1508.05647

pmid: 26764853

arXiv: http://arxiv.org/abs/1508.05647

Population annealing: Theory and application in spin glasses

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Abstract

Population annealing is an efficient sequential Monte Carlo algorithm for simulating equilibrium states of systems with rough free energy landscapes. The theory of population annealing is presented, and systematic and statistical errors are discussed. The behavior of the algorithm is studied in the context of large-scale simulations of the three-dimensional Ising spin glass and the performance of the algorithm is compared to parallel tempering. It is found that the two algorithms are similar in efficiency though with different strengths and weaknesses.

16 pages, 10 figures, 4 tables

Related Organizations

Texas A&M Research Foundation
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University of Massachusetts System
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Santa Fe Institute
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Coventry University
Texas A&M University
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Keywords

Statistical Mechanics (cond-mat.stat-mech), FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics

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