Geometric Cluster Algorithm for Interacting Fluids

Abstract

We discuss a new Monte Carlo algorithm for the simulation of complex fluids. This algorithm employs geometric operations to identify clusters of particles that can be moved in a rejection-free way. It is demonstrated that this geometric cluster algorithm (GCA) constitutes the continuum generalization of the Swendsen-Wang and Wolff cluster algorithms for spin systems. Because of its nonlocal nature, it is particularly well suited for the simulation of fluid systems containing particles of widely varying sizes. The efficiency improvement with respect to conventional simulation algorithms is a rapidly growing function of the size asymmetry between the constituents of the system. We study the cluster-size distribution for a Lennard-Jones fluid as a function of density and temperature and provide a comparison between the generalized GCA and the hard-core GCA for a size-asymmetric mixture with Yukawa-type couplings.