Cluster Heat Bath Algorithm in Monte Carlo Simulations of Ising Models

Abstract

We have proposed a cluster heat bath method in Monte Carlo simulations of Ising models in which one of the possible spin configurations of a cluster is selected in accordance with its Boltzmann weight. We have argued that the method improves slow relaxation in complex systems and demonstrated it in an axial next-nearest-neighbor Ising(ANNNI) model in two-dimensions.