Nonadiabatic force matching for alchemical free-energy estimation

TL;DR

This paper introduces a novel nonadiabatic force matching method using flow-based generative models to efficiently estimate free-energy differences in alchemical transformations, reducing computational cost while maintaining accuracy.

Contribution

It presents a new approach combining nonadiabatic force estimation with flow-based models for alchemical free-energy calculations, improving efficiency over traditional methods.

Findings

Reduces simulation cost significantly compared to thermodynamic integration.

Provides bounds on free energy that converge to the exact value.

Maintains negligible accuracy loss with shorter trajectories.

Abstract

We propose a method to compute free-energy differences from nonadiabatic alchemical transformations using flow-based generative models. The method, nonadiabatic force matching, hinges on estimating the dissipation along an alchemical switching process in terms of a nonadiabatic force field that can be learned through stochastic flow matching. The learned field can be used in conjunction with short-time trajectory data to evaluate upper and lower bounds on the alchemical free energy that variationally converge to the exact value if the field is optimal. Applying the method to evaluate the alchemical free energy of atomistic models shows that it can substantially reduce the simulation cost of a free-energy estimate at negligible loss of accuracy when compared with thermodynamic integration.