The computation of averages from equilibrium and nonequilibrium Langevin molecular dynamics

TL;DR

This paper analyzes numerical methods for Langevin and overdamped Langevin dynamics used in thermodynamic sampling, providing error estimates and comparing biases for different splitting schemes, including nonequilibrium cases.

Contribution

It introduces error estimates for invariant measures of splitting methods and compares their sampling biases, especially in nonequilibrium steady states.

Findings

Error bounds for invariant measures at small stepsize

Comparison of sampling biases among splitting methods

Numerical validation of theoretical results

Abstract

We consider numerical methods for thermodynamic sampling, i.e. computing sequences of points distributed according to the Gibbs-Boltzmann distribution, using Langevin dynamics and overdamped Langevin dynamics (Brownian dynamics). A wide variety of numerical methods for Langevin dynamics may be constructed based on splitting the stochastic differential equations into various component parts, each of which may be propagated exactly in the sense of distributions. Each such method may be viewed as generating samples according to an associated invariant measure that differs from the exact canonical invariant measure by a stepsize-dependent perturbation. We provide error estimates a la Talay-Tubaro on the invariant distribution for small stepsize, and compare the sampling bias obtained for various choices of splitting method. We further investigate the overdamped limit and apply the methods in the context of driven systems where the goal is sampling with respect to a nonequilibrium steady state. Our analyses are illustrated by numerical experiments.