Microscopic Mechanisms of Diffusion Dynamics: A Comparative Efficiency Study of Event-Chain Monte Carlo Variants in Dense Hard Disk Systems

TL;DR

This paper compares different event-chain Monte Carlo algorithms to understand their microscopic diffusion mechanisms in dense hard disk systems, aiming to optimize simulation efficiency and deepen understanding of structural relaxation in packed systems.

Contribution

It introduces a systematic comparison of Newtonian and straight event-chain algorithms, revealing how parameters like chain length and system phase affect diffusion efficiency in dense systems.

Findings

Efficiency depends on chain length and system phase.

Hopping motion significantly influences diffusion dynamics.

Optimizing parameters can improve simulation performance.

Abstract

In molecular simulations, efficient methods for investigating equilibration and slow relaxation in dense systems are crucial yet challenging. This study focuses on the diffusional characteristics of monodisperse hard disk systems at equilibrium, comparing novel methodologies of event-chain Monte Carlo variants, specifically the Newtonian event-chain and straight event-chain algorithms. We systematically analyze both event-based and CPU time-based efficiency in liquid and solid phases, aiming to elucidate the microscopic mechanisms underlying structural relaxation. Our results demonstrate how chain length or duration, system size, and phase state influence the efficiency of diffusion dynamics, including hopping motion. This work provides insights into optimizing simulation techniques for highly packed systems and has the potential to improve our understanding of diffusion dynamics even in complex many-body systems.