Diffusion processes with Gamma-distributed resetting and non-instantaneous returns

TL;DR

This paper studies a Brownian particle with stochastic resetting governed by a Gamma distribution, analyzing how non-instantaneous returns and the distribution parameters influence the steady state and search efficiency.

Contribution

It introduces a model with Gamma-distributed resetting intervals and finite-velocity returns, revealing the conditions under which the steady state is unaffected by return velocity.

Findings

The process reaches a non-equilibrium steady state for all Gamma shape parameters.

The stationary distribution depends on the return velocity, except at a specific shape parameter.

Explicit expressions for the mean first passage time are derived and validated by simulations.

Abstract

We consider the dynamical evolution of a Brownian particle undergoing stochastic resetting, meaning that after random periods of time it is forced to return to the starting position. The intervals after which the random motion is stopped are drawn from a Gamma distribution of shape parameter $\alpha$ and scale parameter $r$, while the return motion is performed at constant velocity $v$, so that the time cost for a reset is correlated to the last position occupied during the stochastic phase. We show that for any value of $\alpha$ the process reaches a non-equilibrium steady state and unveil the dependence of the stationary distribution on $v$. Interestingly, there is a single value of $\alpha$ for which the steady state is unaffected by the return velocity. Furthermore, we consider the efficiency of the search process by computing explicitly the mean first passage time. All our findings are corroborated by numerical simulations.