A Monte Carlo Algorithm for Sampling Rare Events: Application to a Search for the Griffiths Singularity
Disordered Systems and Neural Networks
2009-11-13 v1 Statistical Mechanics
Abstract
We develop a recently proposed importance-sampling Monte Carlo algorithm for sampling rare events and quenched variables in random disordered systems. We apply it to a two dimensional bond-diluted Ising model and study the Griffiths singularity which is considered to be due to the existence of rare large clusters. It is found that the distribution of the inverse susceptibility has an exponential tail down to the origin which is considered the consequence of the Griffiths singularity.
Cite
@article{arxiv.0711.0870,
title = {A Monte Carlo Algorithm for Sampling Rare Events: Application to a Search for the Griffiths Singularity},
author = {Koji Hukushima and Yukito Iba},
journal= {arXiv preprint arXiv:0711.0870},
year = {2009}
}
Comments
10 pages, Proceedings of the International Workshop on Statistical-Mechanical Informatics 2007, Kyoto (Japan) September 16-19, 2007