1997/08/05 by Bernd A. Berg
Mathematics · Physics and Astronomy · #Markov Chains and Monte Carlo Methods #Statistical Methods and Bayesian Inference #Theoretical and Computational Physics #cond-mat #hep-lat
paper · pdf · doi:10.1016/s0920-5632(97)00962-6
published as Nucl.Phys.Proc.Suppl. 63 (1998) 982-984 · 4 pages latex, Slightly expanded contribution to the LAT97 Edinburgh conference, to appear in the proceedings, Nucl. Phys. B (Proc. Suppl.)
arxiv created 1997/08/05 · openalex publication_date 1998/04/01 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Monte Carlo (MC) simulations of many systems, in particular those with conflicting constraints, can be considerably speeded up by using multicanonical or related methods. Some of these approaches sample with a-priori unknown weight factors. After introducing the concept, I shall focus on two aspects: (i) Opinions about the optimal choice of weight factors. (ii) Methods to get weight factor estimates, with emphasize on a multicanonical recursion.