Broad histogram relation for the bond number and its applications
arXiv:cond-mat/0205578 · doi:10.1103/PhysRevE.66.036704
Abstract
We discuss Monte Carlo methods based on the cluster (graph) representation for spin models. We derive a rigorous broad histogram relation (BHR) for the bond number; a counterpart for the energy was derived by Oliveira previously. A Monte Carlo dynamics based on the number of potential moves for the bond number is proposed. We show the efficiency of the BHR for the bond number in calculating the density of states and other physical quantities.
7 pages, 7 figures
References in corpus (4)
- Determining the density of states for classical statistical models: A random walk algorithm to produce a flat histogram
- Combination of improved multibondic method and the Wang-Landau method
- Simulation of Potts models with real q and no critical slowing down
- Probability-Changing Cluster Algorithm: Study of Three-Dimensional Ising Model and Percolation Problem
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