2001/04/23 by Jian‐Sheng Wang, Jian-Sheng Wang, Robert H. Swendsen · 4 citations
Mathematics · Physics and Astronomy · #Artificial intelligence #Computer science #Dynamic Monte Carlo method #Histogram #Hybrid Monte Carlo #Markov chain Monte Carlo #Mathematics #Monte Carlo integration #Monte Carlo method #Monte Carlo method in statistical physics #Monte Carlo molecular modeling #Physics #Quantum Monte Carlo #Scientific Research and Discoveries #Statistical physics #Statistics #Stochastic processes and statistical mechanics #Theoretical and Computational Physics #cond-mat.stat-mech
paper · pdf · doi:10.1023/a:1013180330892
published as J. Stat. Phys. vol 106, 245 (2002) · 38 LaTeX pages
arxiv created 2001/04/23 · openalex publication_date 2002/01/01 · arxiv updated 2011/12/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We present a formalism of the transition matrix Monte Carlo method. A stochastic matrix in the space of energy can be estimated from Monte Carlo simulation. This matrix is used to compute the density of states, as well as to construct multi-canonical and equal-hit algorithms. We discuss the performance of the methods. The results are compared with single histogram method, multi-canonical method, and other methods. In many aspects, the present method is an improvement over the previous methods. PACS numbers: 02.70.Tt, 05.10.Ln, 05.50.+q. Keywords: Monte Carlo method, flat histogram, multi-canonical ensemble.