Reduced critical slowing down for statistical physics simulations

Kurt Langfeld, Pavel Buividovich, P. E. L. Rakow, and James Roscoe
Phys. Rev. E 106, 054139 – Published 16 November 2022

Abstract

Wang-Landau simulations offer the possibility to integrate explicitly over a collective coordinate and stochastically over the remainder of configuration space. We propose to choose the so-called “slow mode,” which is responsible for large autocorrelation times and thus critical slowing down, for collective integration. We study this proposal for the Ising model and the linear-log-relaxation (LLR) method as simulation algorithm. We first demonstrate supercritical slowing down in a phase with spontaneously broken symmetry and for the heat-bath algorithms, for which autocorrelation times grow exponentially with system size. By contrast, using the magnetization as collective coordinate, we present evidence that supercritical slowing down is absent. We still observe a polynomial increase of the autocorrelation time with volume (critical slowing down), which is, however, reduced by orders of magnitude when compared to local update techniques.

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  • Received 22 May 2022
  • Accepted 23 October 2022

DOI:https://doi.org/10.1103/PhysRevE.106.054139

©2022 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsParticles & FieldsCondensed Matter, Materials & Applied Physics

Authors & Affiliations

Kurt Langfeld

  • School of Mathematics, University of Leeds, Leeds, LS2 9JT, United Kingdom

Pavel Buividovich, P. E. L. Rakow, and James Roscoe

  • Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZX, United Kingdom

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Issue

Vol. 106, Iss. 5 — November 2022

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