Kinetic event-chain algorithm for active matter

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Authors: Nico Schaffrath, Thevashangar Sathiyanesan, Tobias A. Kampmann, Jan Kierfeld
Cited by: 0
References: 42

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.

Fields of Study & Subjects

Micro and Nano Robotics Pickering emulsions and particle stabilization Advanced Thermodynamics and Statistical Mechanics

Publication details

Journal / source
Physical Review Research
Volume
8
Issue
2
Publication date
3 May 2026
Language
EN