Nonlocal Monte Carlo algorithms for statistical physics applications

Wolfhard Janke

Mathematics and Computers in Simulation (MATCOM), 1998, vol. 47, issue 2, 329-346

Abstract: After a brief general overview of Monte Carlo computer simulations in statistical physics, special emphasis is placed on applications to phase transitions and critical phenomena. Here, standard simulations employing local update algorithms are severely hampered by the problem of critical slowing down, that is by strong correlations between successively generated data. It is shown that this problem can be greatly reduced by using nonlocal update techniques such as cluster and multigrid algorithms. The general ideas are illustrated for simple lattice spin models and Euclidean path integrals.

Keywords: Monte Carlo simulations; Importance sampling; Cluster algorithms; Multigrid techniques; Phase transitions; Critical phenomena (search for similar items in EconPapers)
Date: 1998
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475498001098
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:47:y:1998:i:2:p:329-346

DOI: 10.1016/S0378-4754(98)00109-8

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().