Memory-induced active particle ratchets: Mean currents and large deviations

TL;DR

This paper investigates a stochastic model of active particles with memory effects, deriving explicit formulas for mean currents and analyzing large deviations to understand the system's non-equilibrium behavior.

Contribution

It introduces a renewal-theory framework for analyzing large deviations in active particle ratchets with memory effects, providing explicit mean current formulas.

Findings

Explicit mean current expression for exponential reorientation times

Development of a renewal-theory framework for large deviations

Discussion of potential dynamical phase transitions

Abstract

We analyse a continuous-time random walk model with stochastic reversals of direction. There is no external potential but the reorientation mechanism generates a non-zero current from asymmetry in the forward and backward waiting-time distributions (even when they have the same mean); the system can therefore can be considered as a type of active particle ratchet. We derive an explicit expression for the mean ratchet current with exponentially distributed reorientation times and also develop a general renewal-theory framework to obtain the full large deviations, using this to comment on the possibility of dynamical phase transitions.