Rejection-free Monte-Carlo sampling for general potentials

TL;DR

This paper introduces a rejection-free, event-driven Monte Carlo method for sampling classical systems with smooth potentials, enabling efficient simulations of Lennard-Jones particles without move rejections.

Contribution

The paper presents a novel rejection-free Monte Carlo algorithm with event-driven collision scheduling for smooth potentials, extending the applicability of Monte Carlo sampling.

Findings

Successfully simulated Lennard-Jones particles using the new method

Demonstrated efficiency over traditional rejection-based algorithms

Introduced an event-chain implementation for improved performance

Abstract

A Monte Carlo method to sample the classical configurational canonical ensemble is introduced. In contrast to the Metropolis algorithm, where trial moves can be rejected, in this approach collisions take place. The implementation is event-driven, i.e., at scheduled times the collisions occur. A unique feature of the new method is that smooth potentials (instead of only step-wise changing ones) can be used. Besides an event-driven approach where all particles move simultaneously, we also introduce a straight event-chain implementation. As proof-of-principle a system of Lennard-Jones particles is simulated.