Event-driven Monte Carlo algorithm for general potentials
Statistical Mechanics
2022-08-31 v1 Soft Condensed Matter
Computational Physics
Abstract
We extend the event-chain Monte Carlo algorithm from hard-sphere interactions to the micro-canonical ensemble (constant potential energy) for general potentials. This event-driven Monte Carlo algorithm is non-local, rejection-free, and allows for the breaking of detailed balance. The algorithm uses a discretized potential, but its running speed is asymptotically independent of the discretization. We implement the algorithm for the cut-off linear potential, and discuss its possible implementation directly in the continuum limit.
Cite
@article{arxiv.1111.6964,
title = {Event-driven Monte Carlo algorithm for general potentials},
author = {Etienne P. Bernard and Werner Krauth},
journal= {arXiv preprint arXiv:1111.6964},
year = {2022}
}
Comments
3 pages 4 figures, brief report