Population annealing: Theory and application in spin glasses

Wenlong Wang, Jonathan Machta, and Helmut G. Katzgraber

Phys. Rev. E 92, 063307 – Published 16 December 2015

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.

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Received 23 August 2015

DOI:https://doi.org/10.1103/PhysRevE.92.063307

Authors & Affiliations

Wenlong Wang^1,*, Jonathan Machta^1,2,†, and Helmut G. Katzgraber^3,4,2,5

¹Department of Physics, University of Massachusetts, Amherst, Massachusetts 01003, USA
²Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA
³Department of Physics and Astronomy, Texas A&M University, College Station, Texas 77843-4242, USA
⁴Materials Science and Engineering, Texas A&M University, College Station, Texas 77843, USA
⁵Applied Mathematics Research Centre, Coventry University, Coventry, CV1 5FB, England

^*wenlong@physics.umass.edu
^†machta@physics.umass.edu

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Vol. 92, Iss. 6 — December 2015

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