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arXiv · 2111.06760

Kinetic Event-Chain Algorithm for Active Matter

Nico Schaffrath·Thevashangar Sathiyanesan·Tobias A. Kampmann·Jan Kierfeld
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Abstract

We present a cluster kinetic Monte-Carlo algorithm for active matter systems of self-propelled particles with special focus on steric interactions. The kinetic event-chain algorithm is based on the event-chain Monte-Carlo method and is applied to active Brownian disks in two dimensions. The algorithm assigns Monte-Carlo moves of active disks a mean time based on a comparison between Brownian dynamics and the dynamics of the event-chain Monte-Carlo method. This time is used to perform diffusional rotation of their propulsion force. We show that the algorithm correctly and efficiently reproduces various physical results ranging from single-particle dynamics to many-body-effects. In particular, we reproduce the phase diagram of active disks and the motility-induced phase separated region with high accuracy. The kinetic event-chain algorithm is shown to be much faster - at comparable accuracy - than (event-driven) Brownian dynamics algorithms, enabling large-scale simulations up to giant systems with $10^5$ particles on standard desktop hardware.

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Nico Schaffrath, Thevashangar Sathiyanesan, Tobias A. Kampmann, Jan Kierfeld. 2021-11-12. Kinetic Event-Chain Algorithm for Active Matter. https://doi.org/10.1103/hhbb-ph5s

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