Volume 117, Number 3, February 2017
|Number of page(s)||7|
|Published online||16 March 2017|
Event-chain Monte Carlo algorithms for three- and many-particle interactions
1 Physics Department, TU Dortmund University - 44221 Dortmund, Germany
2 Orange Labs - 44 avenue de la République, CS 50010, 92326 Châtillon CEDEX, France
3 Laboratoire de Physique Statistique, Ecole Normale Supérieure/PSL Research University, UPMC, Université Paris Diderot, CNRS - 24 rue Lhomond, 75005 Paris, France
Received: 24 November 2016
Accepted: 28 February 2017
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.
PACS: 05.10.Ln – Monte Carlo methods / 02.70.Tt – Justifications or modifications of Monte Carlo methods / 64.70.M- – Transitions in liquid crystals
© EPLA, 2017
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