Optimal Modification Factor and Convergence of the Wang-Landau Algorithm
| dc.creator | Zhou, Chenggang | |
| dc.creator | Su, Jia | |
| dc.date | 2008-10-01 | |
| dc.date.accessioned | 2026-07-07T10:12:37Z | |
| dc.date.available | 2026-07-07T10:12:37Z | |
| dc.description | We propose a strategy to achieve the fastest convergence in the Wang-Landau algorithm with varying modification factors. With this strategy, the convergence of a simulation is at least as good as the conventional Monte Carlo algorithm, i.e. the statistical error vanishes as $1/\sqrt{t}$, where $t$ is a normalized time of the simulation. However, we also prove that the error cannot vanish faster than $1/t$. Our findings are consistent with the $1/t$ Wang-Landau algorithm discovered recently, and we argue that one needs external information in the simulation to beat the conventional Monte Carlo algorithm. | |
| dc.description | 19 pages and 3 figures, to be published in Phys. Rev. E | |
| dc.identifier | https://arxiv.org/abs/0810.0158 | |
| dc.identifier | http://arxiv.org/abs/0810.0158 | |
| dc.identifier | Phys. Rev. E 78, 046705 (2008) | |
| dc.identifier | doi:10.1103/PhysRevE.78.046705 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/172241 | |
| dc.subject | Statistical Mechanics | |
| dc.title | Optimal Modification Factor and Convergence of the Wang-Landau Algorithm | |
| dc.type | text |