Avoiding unphysical kinetic traps in Monte Carlo simulations of strongly attractive particles

We introduce a virtual- move Monte Carlo algorithm for systems of pairwise- interacting particles. This algorithm facilitates the simulation of particles possessing attractions of short range and arbitrary strength and geometry, an important realization being self- assembling particles endowed with strong, short- ranged, and angularly specific ( patchy) attractions. Standard Monte Carlo techniques employ sequential updates of particles and can suffer from low acceptance rates when attractions are strong. In this event, collective motion can be strongly suppressed. Our algorithm avoids this problem by proposing simultaneous moves of collections (clusters) of particles according to gradients of interaction energies. One particle first executes a virtual trial move. We determine which of its neighbors move in a similar fashion by calculating individual bond energies before and after the proposed move. We iterate this procedure and update simultaneously the positions of all affected particles. Particles move according to an approximation of realistic dynamics without requiring the explicit computation of forces and without the step size restrictions required when integrating equations of motion. We employ a size- and shape- dependent damping of cluster movements, motivated by collective hydrodynamic effects neglected in simple implementations of Brownian dynamics. We discuss the virtual- move algorithm in the context of other Monte Carlo cluster- move schemes and demonstrate its utility by applying it to a model of biological self- assembly. (C) 2007 American Institute of Physics. [DOI: 10.1063/ 1.2790421]