Novel Monte Carlo algorithms and their applications
Statistical Mechanics
2009-11-07 v1
Abstract
We describe a generalized scheme for the probability-changing cluster (PCC) algorithm, based on the study of the finite-size scaling property of the correlation ratio, the ratio of the correlation functions with different distances. We apply this generalized PCC algorithm to the two-dimensional 6-state clock model. We also discuss the combination of the cluster algorithm and the extended ensemble method. We derive a rigorous broad histogram relation for the bond number. A Monte Carlo dynamics based on the number of potential moves for the bond number is proposed, and applied to the three-dimensional Ising and 3-state Potts models.
Cite
@article{arxiv.cond-mat/0211035,
title = {Novel Monte Carlo algorithms and their applications},
author = {Yutaka Okabe and Yusuke Tomita and Chiaki Yamaguchi},
journal= {arXiv preprint arXiv:cond-mat/0211035},
year = {2009}
}
Comments
13 pages including 7 eps figures, proceedings of StatPhys-Taiwan-2002, to appear in Physica A