Exploring High Dimensional Free Energy Landscapes: Temperature Accelerated Sliced Sampling

TL;DR

The paper introduces TASS, a novel sampling method combining temperature acceleration, umbrella sampling, and metadynamics, enabling efficient exploration of high-dimensional free energy landscapes in molecular simulations.

Contribution

TASS is a new method that efficiently samples many collective variables, improving convergence speed and applicability in ab initio molecular dynamics.

Findings

TASS achieves rapid free energy convergence.

It effectively samples broad and unbound free energy basins.

The method is practical for use with ab initio MD.

Abstract

Biased sampling of collective variables is widely used to accelerate rare events in molecular simulations and to explore free energy surfaces. However, computational efficiency of these methods decreases with increasing number of collective variables, which severely limits the predictive power of the enhanced sampling approaches. Here we propose a method called Temperature Accelerated Sliced Sampling (TASS) that combines temperature accelerated molecular dynamics with umbrella sampling and metadynamics to sample the collective variable space in an efficient manner. The presented method can sample a large number of collective variables and is advantageous for controlled exploration of broad and unbound free energy basins. TASS is also shown to achieve quick free energy convergence and is practically usable with ab initio molecular dynamics techniques.