Universal criterion for selective outcomes under stochastic resetting

Resetting plays a pivotal role in optimizing the completion time of complex first-passage processes with single or multiple outcomes and exit possibilities. While it is well established that the coefficient of variation-a statistical dispersion defined as a ratio of the fluctuations over the mean of the first-passage time-must be larger than unity for resetting to be beneficial for any outcome averaged over all the possibilities, the same cannot be said while conditioned on a particular outcome. The purpose of this article is to derive a universal condition that reveals that two statistical metrics-the mean and coefficient of variation of the conditional times-come together to determine when resetting can expedite the completion of a selective outcome, and furthermore can govern the biasing between preferential and nonpreferential outcomes. The universality of this result is demonstrated for a one-dimensional diffusion process subjected to resetting with two absorbing boundaries.

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Publication Details

Journal
Physical review. E
Published
2025-08-18
DOI
https://doi.org/10.1103/p3yc-kmt1
Citations
2
Primary Topic
Diffusion and Search Dynamics
Type
article
Field-Weighted Citation Impact
1.61
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article

Universal criterion for selective outcomes under stochastic resetting

Leonardo Dagdug, Dibakar Ghosh, A. Pal, Denis Boyer et al.
2 citations
Physical review. E
Diffusion and Search Dynamics
1.61
article

Universal criterion for selective outcomes under stochastic resetting

Leonardo Dagdug, Dibakar Ghosh, A. Pal, Denis Boyer, Suvam Pal
article en
2 citations

Abstract

Resetting plays a pivotal role in optimizing the completion time of complex first-passage processes with single or multiple outcomes and exit possibilities. While it is well established that the coefficient of variation-a statistical dispersion defined as a ratio of the fluctuations over the mean of the first-passage time-must be larger than unity for resetting to be beneficial for any outcome averaged over all the possibilities, the same cannot be said while conditioned on a particular outcome. The purpose of this article is to derive a universal condition that reveals that two statistical metrics-the mean and coefficient of variation of the conditional times-come together to determine when resetting can expedite the completion of a selective outcome, and furthermore can govern the biasing between preferential and nonpreferential outcomes. The universality of this result is demonstrated for a one-dimensional diffusion process subjected to resetting with two absorbing boundaries.

Physical review. EVol. 112(3)
Homi Bhabha National Institute (IN), Universidad Autónoma Metropolitana (MX), Institute of Mathematical Sciences (IN), Indian Statistical Institute (IN), Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 15%
Diffusion and Search Dynamics
1.61
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Universal criterion for selective outcomes under stochastic resetting — Leonardo Dagdug, Dibakar Ghosh, et al. · Physical review. E (2025) | TGRS Research Map | TGRS