Generalized-Ensemble Algorithms: Enhanced Sampling Techniques for Monte Carlo and Molecular Dynamics Simulations
| dc.creator | Okamoto, Y. | |
| dc.date | 2003-08-18 | |
| dc.date.accessioned | 2026-07-07T09:46:13Z | |
| dc.date.available | 2026-07-07T09:46:13Z | |
| dc.description | In complex systems with many degrees of freedom such as spin glass and biomolecular systems, conventional simulations in canonical ensemble suffer from the quasi-ergodicity problem. A simulation in generalized ensemble performs a random walk in potential energy space and overcomes this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review the generalized-ensemble algorithms. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present five new generalized-ensemble algorithms which are extensions of the above methods. | |
| dc.description | 28 pages, (LaTeX); a review article to appear in Journal of Molecular Graphics and Modelling | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0308360 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0308360 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/163453 | |
| dc.subject | Statistical Mechanics | |
| dc.subject | Quantitative Methods | |
| dc.title | Generalized-Ensemble Algorithms: Enhanced Sampling Techniques for Monte Carlo and Molecular Dynamics Simulations | |
| dc.type | text |