Kinetic Monte Carlo Algorithms for Active Matter Systems
| Autor: | Olivier Dauchot, Juliane U. Klamser, Julien Tailleur |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Physics
Statistical Mechanics (cond-mat.stat-mech) Active particles Ratchet General Physics and Astronomy FOS: Physical sciences Condensed Matter - Soft Condensed Matter Active matter Soft Condensed Matter (cond-mat.soft) Limit (mathematics) Kinetic Monte Carlo Algorithm Scaling Mixing (physics) Brownian motion Condensed Matter - Statistical Mechanics |
| Zdroj: | Physical review letters. 127(15) |
| ISSN: | 1079-7114 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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