Computation of free energy profiles with parallel adaptive dynamics

TL;DR

This paper introduces a unified adaptive framework for computing free energy profiles using parallel dynamics, providing convergence proofs and improved replica selection methods, demonstrated on a conformational change model.

Contribution

It unifies adaptive free energy computation methods and enhances parallel implementation with selection mechanisms, supported by convergence analysis.

Findings

Parallel implementation is natural and effective.

Selection mechanisms improve replica interactions.

Demonstrated on a conformational change model.

Abstract

We propose a formulation of adaptive computation of free energy differences, in the ABF or nonequilibrium metadynamics spirit, using conditional distributions of samples of configurations which evolve in time. This allows to present a truly unifying framework for these methods, and to prove convergence results for certain classes of algorithms. From a numerical viewpoint, a parallel implementation of these methods is very natural, the replicas interacting through the reconstructed free energy. We show how to improve this parallel implementation by resorting to some selection mechanism on the replicas. This is illustrated by computations on a model system of conformational changes.