Inferring equilibrium transition rates from nonequilibrium protocols

TL;DR

This paper introduces a thermodynamic framework to infer equilibrium transition rates from nonequilibrium trajectories driven by time-dependent forces, improving accuracy over traditional phenomenological methods.

Contribution

The authors develop a nonequilibrium transition state theory using stochastic thermodynamics to estimate transition rates from driven trajectories, surpassing Bell's law-based approaches.

Findings

Accurately infers transition rates in driven systems.

Demonstrates effectiveness in particle pulling and polymer examples.

Outperforms phenomenological approaches like Bell's law.

Abstract

We develop a theory for inferring equilibrium transition rates from trajectories driven by a time dependent force using results from stochastic thermodynamics. Applying the Kawasaki relation to approximate the nonequilibrium distribution function in terms of the equilibrium distribution function and the excess dissipation, we formulate a nonequilibrium transition state theory to estimate the rate enhancement over the equilibrium rate due to the nonequilibrium protocol. We demonstrate the utility of our theory in examples of pulling of harmonically trapped particles in 1 and 2 dimensions, as well as a semi-flexible polymer with a reactive linker in 3 dimensions. In all cases we find that we are able to infer the transition rates more effectively than phenomenological approaches based on Bell's law. We expect our thermodynamic approach will find use in both molecular simulation and force spectroscopy experiments.