A Monte Carlo Algorithm for Sampling Rare Events: Application to a Search for the Griffiths Singularity

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.

10 pages, Proceedings of the International Workshop on Statistical-Mechanical Informatics 2007, Kyoto (Japan) September 16-19, 2007

References in corpus (3)

• Universality-class dependence of energy distributions in spin glasses
• Probing the tails of the ground state energy distribution for the directed polymer in a random medium of dimension $d=1,2,3$ via a Monte-Carlo procedure in the disorder
• Probing tails of energy distributions using importance-sampling in the disorder with a guiding function

Cited by in corpus (2)

• Distribution of Lee-Yang zeros and Griffiths singularities in the $\pm J$ model of spin glasses
• Testing Error Correcting Codes by Multicanonical Sampling of Rare Events