Kinetic Monte-Carlo Algorithms for Active-Matter systems
Statistical Mechanics
2021-12-30 v2 Soft Condensed Matter
Abstract
We study kinetic Monte-Carlo (KMC) descriptions of active particles. By relying on large discrete time steps, KMC algorithms accelerate the relaxational dynamics of active systems towards their steady-state. We show, however, that their continuous-time limit is ill-defined, leading to the vanishing of trademark behaviors of active matter such as the motility-induced phase separation, ratchet effects, as well as to a diverging mechanical pressure. We show how mixing passive steps with active ones regularizes this behavior, leading to a well-defined continuous-time limit. We propose new AKMC algorithms whose continuous-time limits lead to the active dynamics of Active-Ornstein Uhlenbeck, Active Brownian, and Run-and-Tumbles particles.
Cite
@article{arxiv.2103.09001,
title = {Kinetic Monte-Carlo Algorithms for Active-Matter systems},
author = {Juliane U. Klamser and Olivier Dauchot and Julien Tailleur},
journal= {arXiv preprint arXiv:2103.09001},
year = {2021}
}