Abstract
The development of cluster methods for magnetic systems and their connections with the geometric cluster Monte Carlo algorithm, is discussed. The conventional Monte Carlo simulation is based on the use of random numbers to generate the trial configurations and to decide on their acceptance or rejection. The single-cluster approach is more efficient and easier to implement, and also, it is possible to formulate a multiple-cluster version of the generalized GCA, which illustrates that GCA is a true off-lattice version of the the cluster algorithms. The generalized GCA is the first general rejection-free cluster algorithm for off-lattice system, which can accelerate the simulation of fluids in which the constituents exhibit a large asymmetry.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 20-29 |
| Number of pages | 10 |
| Journal | Computing in Science and Engineering |
| Volume | 8 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 2006 |
Funding
The work described in this article was performed with Jiwen Liu and supported by the US National Science Foundation under CAREER award number DMR-0346914 and grant number CTS-0120978, as well as by the US Department of Energy, Division of Materials Sciences, under award number DEFG02-91ER45439, through the Frederick Seitz Materials Research Laboratory at the University of Illinois at Urbana-Champaign.
ASJC Scopus subject areas
- General Computer Science
- General Engineering