Optimal conditions for first passage of jump processes with resetting

Fuente: arXiv
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Autori principali: Radice, Mattia, Cristadoro, Giampaolo, Thapa, Samudrajit
Natura: Preprint
Pubblicazione: 2024
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author Radice, Mattia
Cristadoro, Giampaolo
Thapa, Samudrajit
author_facet Radice, Mattia
Cristadoro, Giampaolo
Thapa, Samudrajit
contents We investigate the first passage time beyond a barrier located at $b\geq0$ of a random walk with independent and identically distributed jumps, starting from $x_0=0$. The walk is subject to stochastic resetting, meaning that after each step the evolution is restarted with fixed probability $r$. We consider a resetting protocol that is an intermediate situation between a random walk ($r=0$) and an uncorrelated sequence of jumps all starting from the origin ($r=1$), and derive a general condition for determining when restarting the process with $0<r<1$ is more efficient than restarting after each jump. If the mean first passage time of the process in absence of resetting is larger than that of the sequence of jumps, this condition is sufficient to establish the existence of an optimal $0<r^*<1$ that represents the best strategy, outperforming both $r=0$ and $r=1$. Our findings are discussed by considering two important examples of jump processes, for which we draw the phase diagram illustrating the regions of the parameter space where resetting with some $0<r^*<1$ is optimal.
format Preprint
id arxiv_https___arxiv_org_abs_2410_05835
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal conditions for first passage of jump processes with resetting
Radice, Mattia
Cristadoro, Giampaolo
Thapa, Samudrajit
Statistical Mechanics
Probability
We investigate the first passage time beyond a barrier located at $b\geq0$ of a random walk with independent and identically distributed jumps, starting from $x_0=0$. The walk is subject to stochastic resetting, meaning that after each step the evolution is restarted with fixed probability $r$. We consider a resetting protocol that is an intermediate situation between a random walk ($r=0$) and an uncorrelated sequence of jumps all starting from the origin ($r=1$), and derive a general condition for determining when restarting the process with $0<r<1$ is more efficient than restarting after each jump. If the mean first passage time of the process in absence of resetting is larger than that of the sequence of jumps, this condition is sufficient to establish the existence of an optimal $0<r^*<1$ that represents the best strategy, outperforming both $r=0$ and $r=1$. Our findings are discussed by considering two important examples of jump processes, for which we draw the phase diagram illustrating the regions of the parameter space where resetting with some $0<r^*<1$ is optimal.
title Optimal conditions for first passage of jump processes with resetting
topic Statistical Mechanics
Probability
url https://arxiv.org/abs/2410.05835