Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method

TL;DR

This paper introduces Well-Tempered Metadynamics, a flexible and convergent free-energy calculation method that adaptively biases collective variables, allowing precise control and efficient sampling of relevant regions, demonstrated on alanine dipeptide.

Contribution

It presents a new metadynamics-based approach with tunable parameters and rigorous convergence control, unifying existing sampling methods.

Findings

Effective reconstruction of alanine dipeptide free energy landscape

Convergence and error control are straightforward and rigorous

Parameters can be tuned to focus on relevant regions

Abstract

We present a method for determining the free energy dependence on a selected number of collective variables using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting cases. Convergence and errors can be rigorously and easily controlled. The parameters of the simulation can be tuned so as to focus the computational effort only on the physically relevant regions of the order parameter space. The algorithm is tested on the reconstruction of alanine dipeptide free energy landscape.