Cluster Monte Carlo algorithms

dc.creatorKrauth, Werner
dc.date2003-11-27
dc.date.accessioned2026-07-07T02:54:59Z
dc.date.available2026-07-07T02:54:59Z
dc.descriptionIn recent years, a better understanding of the Monte Carlo method has provided us with many new techniques in different areas of statistical physics. Of particular interest are so called cluster methods, which exploit the considerable algorithmic freedom given by the detailed balance condition. Cluster algorithms appear, among other systems, in classical spin models, such as the Ising model, in lattice quantum models (bosons, quantum spins and related systems) and in hard spheres and other `entropic' systems for which the configurational energy is either zero or infinite. In this chapter, we discuss the basic idea of cluster algorithms with special emphasis on the pivot cluster method for hard spheres and related systems, for which several recent applications are presented.We provide less technical detail but more context than in the original papers.
dc.descriptionChapter of `New Optimization Algorithms in Physics', edited by A. K. Hartmann and H. Rieger, (Wiley-VCh). ISBN: 3-527-40406-6, Estimated publishing date: June 2004, see: http://www.wiley-vch.de/publish/en/books/
dc.identifierhttps://arxiv.org/abs/cond-mat/0311623
dc.identifierhttp://arxiv.org/abs/cond-mat/0311623
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/22787
dc.subjectStatistical Mechanics
dc.titleCluster Monte Carlo algorithms
dc.typetext

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