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Dresden 2017 – scientific programme

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DY: Fachverband Dynamik und Statistische Physik

DY 44: Statistical Physics (general)

DY 44.4: Talk

Thursday, March 23, 2017, 10:45–11:00, ZEU 147

Event-chain Monte Carlo algorithms for three- and many-particle interactions — •Tobias A. Kampmann1, Julian Harland1, Manon Michel2,3, and Jan Kierfeld11TU Dortmund University, Dortmund, Germany — 2Orange Labs, Chatillon, France — 3Laboratoire de Physique Statistique, Paris, France

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.

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