Accurate multiple time step in biased molecular simulations

TL;DR

This paper introduces an algorithm that efficiently integrates smooth biasing forces in multiple time step molecular dynamics, significantly speeding up simulations with expensive collective variables, and provides a framework to evaluate sampling accuracy.

Contribution

It presents a simple, effective algorithm for multiple time step biased simulations and a theoretical framework to assess sampling accuracy, enhancing efficiency and reliability.

Findings

Substantial speed-up with GPU-based simulations.

Effective handling of expensive collective variables.

Framework for assessing sampling accuracy.

Abstract

Many recently introduced enhanced sampling techniques are based on biasing coarse descriptors (collective variables) of a molecular system on the fly. Sometimes the calculation of such collective variables is expensive and becomes a bottleneck in molecular dynamics simulations. An algorithm to treat smooth biasing forces within a multiple time step framework is here discussed. The implementation is simple and allows a speed up when expensive collective variables are employed. The gain can be substantial when using massively parallel or GPU-based molecular dynamics software. Moreover, a theoretical framework to assess the sampling accuracy is introduced, which can be used to assess the choice of the integration time step in both single and multiple time step biased simulations.