Enhanced Sampling of Nonequilibrium Steady States

Abstract

We review recent progress in methods for accelerating the convergence of simulations of nonequilibrium systems, specifically nonequilibrium umbrella sampling (NEUS) and forward flux sampling (FFS). These methods account for statistics of dynamical paths between interfaces to enforce sampling of low probability regions of phase space for computing steady-state averages, including transition rates, for systems driven arbitrarily far from equilibrium. Recent advances in NEUS allow for efficient sampling of complex systems by focusing sampling in the vicinity of a one-dimensional manifold (string) that connects regions of interest in phase space; this procedure can be extended to the case of two strings that describe the forward and backward transition ensembles separately, which is useful, as they do not, in general, coincide. We recast FFS in the framework of NEUS to facilitate comparison of the two methods. We conclude by discussing selected applications of interest.