Boosting macroscopic diffusion with local resetting

TL;DR

This paper introduces a local stochastic resetting model that enhances and optimizes the self-diffusivity of agents in diffusive systems, revealing conditions for improved macroscopic transport.

Contribution

It provides an analytic framework showing how local resetting mechanisms can enhance and optimize diffusion, especially with regular resetting site arrangements.

Findings

Resetting enhances self-diffusivity in the model.

Regular arrays of resetting sites optimize diffusion.

Analytic expressions for the self-diffusion coefficient are derived.

Abstract

Stochastic interactions generically enhance self-diffusivity in living and biological systems, e.g. optimizing navigation strategies and controlling material properties of cellular tissues and bacterial aggregates. Despite this, the physical mechanisms underlying this nonequilibrium behavior are poorly understood. Here, we introduce a model of interactions between an agent and its environment in the form of a local stochastic resetting mechanism, in which the agent's position is set to the nearest of a predetermined array of sites with a fixed rate. We derive analytic results for the self-diffusion coefficient, showing explicitly that this mechanism enhances diffusivity. Strikingly, we show analytically that this enhancement is optimized by regular arrays of resetting sites. Altogether, our results ultimately provide the conditions for the optimization of the macroscopic transport properties of diffusive systems with local random binding interactions.