Publication Date
2001
Journal or Book Title
Physics Review Letters
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.
Volume
87
Issue
16
Recommended Citation
Prokof'ev, Nikolai and Svistunov, Boris, "Worm Algorithms for Classical Statistical Models" (2001). Physics Review Letters. 1134.
Retrieved from https://scholarworks.umass.edu/physics_faculty_pubs/1134
Comments
This is the pre-published version harvested from ArXiv. The published version is located at http://prl.aps.org/abstract/PRL/v87/i16/e160601