Autonomous Ratcheting by Stochastic Resetting

Abstract

We propose a generalization of the stochastic resetting mechanism for a Brownian particle diffusing in a one-dimensional periodic potential: randomly in time, the particle gets reset at the bottom of the potential well it was in. Numerical simulations show that in mirror asymmetric potentials, stochastic resetting rectifies the particle's dynamics, with maximum drift speed for an optimal average resetting time. Accordingly, an unbiased Brownian tracer diffusing on an asymmetric substrate can rectify its motion by adopting an adaptive stop-and-go strategy. Our proposed ratchet mechanism can model directed autonomous motion of molecular motors and micro-organisms

Journal of Chemical Physics 2023 (in press)

References in corpus (5)

• Artificial Brownian motors: Controlling transport on the nanoscale
• First Passage Under Restart
• First order transition for the optimal search time of Lévy flights with resetting
• Optimal mean first-passage time for a Brownian searcher subjected to resetting: experimental and theoretical results
• A dynamical model for Brownian molecular motors driven by inelastic electron tunneling

Cited by in corpus (5)

• Search with stochastic home-returns can expedite classical first passage under resetting
• Large Deviations in Switching Diffusion: from Free Cumulants to Dynamical Transitions
• Ratchet-mediated resetting: Current, efficiency, and exact solution
• Arcsine laws for Brownian motion with Poissonian resetting
• Fluctuations in first passage times and utility of resetting protocol in biochemical systems with two-state toggling