Event-chain Monte Carlo algorithms for three- and many-particle interactions
Abstract
We generalize the rejection-free event-chain Monte Carlo algorithm from many particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: (i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; (ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; (iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. The examples demonstrate that the generalization to many-particle interactions broadens the applicability of event-chain algorithms considerably.
Cite
@article{arxiv.1611.09098,
title = {Event-chain Monte Carlo algorithms for three- and many-particle interactions},
author = {Julian Harland and Manon Michel and Tobias A. Kampmann and Jan Kierfeld},
journal= {arXiv preprint arXiv:1611.09098},
year = {2017}
}