Worm Algorithms for Classical Statistical Models

Nikolay Prokof'ev and Boris Svistunov
Phys. Rev. Lett. 87, 160601 – Published 27 September 2001
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Abstract

We show that high-temperature expansions provide a basis for the novel approach to efficient Monte Carlo simulations. “Worm” algorithms utilize the idea of updating closed-path configurations (produced by high-temperature expansions) through the motion of end points of a disconnected path. An amazing result is that local, Metropolis-type schemes using this approach appear to have dynamical critical exponents close to zero (i.e., their efficiency is comparable to the best cluster methods) as proved by finite-size scaling of the autocorrelation time for various universality classes.

  • Received 6 March 2001

DOI:https://doi.org/10.1103/PhysRevLett.87.160601

©2001 American Physical Society

Authors & Affiliations

Nikolay Prokof'ev1 and Boris Svistunov1,2

  • 1Department of Physics, University of Massachusetts, Amherst, Massachusetts 01003
  • 2Russian Research Center “Kurchatov Institute”, 123182 Moscow, Russia

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Issue

Vol. 87, Iss. 16 — 15 October 2001

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