Asynchronous Event-Driven Particle Algorithms

TL;DR

This paper unifies and analyzes three asynchronous event-driven algorithms for simulating interacting particle systems, including molecular dynamics, diffusion kinetic Monte Carlo, and a new stochastic molecular-dynamics method, highlighting their integration and future challenges.

Contribution

It introduces a unifying framework for three particle simulation algorithms and presents a novel stochastic molecular-dynamics algorithm based on Direct Simulation Monte Carlo.

Findings

Unified description of three asynchronous algorithms

Effective combination of event-driven and classical methods

Discussion of future challenges in realistic system simulation

Abstract

We present, in a unifying way, the main components of three asynchronous event-driven algorithms for simulating physical systems of interacting particles. The first example, hard-particle molecular dynamics, is well-known. We also present a recently-developed diffusion kinetic Monte Carlo algorithm, as well as a novel stochastic molecular-dynamics algorithm that builds on the Direct Simulation Monte Carlo. We explain how to effectively combine asynchronous event-driven with classical time-driven or with synchronous event-driven handling. Finally, we discuss some promises and challenges for event-driven simulation of realistic physical systems.