Dynamical transition in the temporal relaxation of stochastic processes under resetting

TL;DR

This paper analyzes how stochastic processes with resetting reach a non-equilibrium steady state, revealing a dynamical transition characterized by a growing core region and a space-dependent transition time, supported by analytical and numerical results.

Contribution

It uncovers a novel relaxation mechanism involving a growing core region and a dynamical transition in stochastic processes with resetting, with analytical and numerical validation.

Findings

Inner core reaches steady state while outside remains transient

Core boundary grows as a power law over time

Large deviation function exhibits a second order discontinuity at critical points

Abstract

A stochastic process, when subject to resetting to its initial condition at a constant rate, generically reaches a non-equilibrium steady state. We study analytically how the steady state is approached in time and find an unusual relaxation mechanism in these systems. We show that as time progresses, an inner core region around the resetting point reaches the steady state, while the region outside the core is still transient. The boundaries of the core region grow with time as power laws at late times. Alternatively, at a fixed spatial point, the system undergoes a dynamical transition from the transient to the steady state at a characteristic space dependent timescale $t^*(x)$. We calculate analytically in several examples the large deviation function associated with this spatio-temporal fluctuation and show that generically it has a second order discontinuity at a pair of critical points characterizing the edges of the inner core. Our results are verified in the numerical simulations of several models, such as simple diffusion and fluctuating one-dimensional interfaces.