Nonequilibrium Optimal Reaction Coordinates for Diffusion

TL;DR

This paper introduces stationary additive eigenvector-based reaction coordinates (addevs) for non-equilibrium diffusion, enabling exact computation of dynamics properties and efficient sampling in classical and quantum systems.

Contribution

It extends the formalism of reaction coordinates to non-equilibrium systems using addevs, providing new models and sampling schemes for classical and quantum diffusion.

Findings

Committors are functions of addevs, allowing exact property computation.

Rates of conditioned processes can be computed on the fly for efficient sampling.

Two families of addev solutions relate to classical and quantum mechanics.

Abstract

Complex multidimensional stochastic dynamics can be approximately described as diffusion along reaction coordinates (RCs). If the RCs are optimally selected, the diffusive model allows one to compute important properties of the dynamics exactly. The committor is a primary example of an optimal RC. Recently, additive eigenvectors (addevs) have been introduced in order to extend the formalism to non-equilibrium dynamics. An addev describes a sub-ensemble of trajectories of a stochastic process together with an optimal RC. The sub-ensemble is conditioned to have a single RC optimal for both the forward and time-reversed non-equilibrium dynamics of the sub-ensemble. Here we consider stationary addevs and obtain the following results. We show that the forward and time-reversed committors are functions of the addev, meaning a diffusive model along an addev RC can be used to compute important properties of non-equilibrium dynamics exactly. The rates of the conditioned stochastic process, describing an addev sub-ensemble, can be computed ``on the fly'', thus allowing efficient sampling schemes. We obtain two families of addev solutions for diffusion. The first is described by equations of classical mechanics, while the second can be approximated by quantum mechanical equations. We show how the potential can be introduced into the formalism self-consistently. The developments are illustrated on simple examples. The two addev families provide stochastic models together with optimal RCs and new sampling schemes for classical and quantum mechanical systems. It suggests that the conditioned stochastic processes defined by addevs are suitable for description of dynamics of physical origin.