Universal criterion for selective outcomes under stochastic resetting
Article Type
Research Article
Publication Title
Physical Review E
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.
DOI
10.1103/p3yc-kmt1
Publication Date
9-3-2025
Recommended Citation
Pal, Suvam; Dagdug, Leonardo; Ghosh, Dibakar; Boyer, Denis; and Pal, Arnab, "Universal criterion for selective outcomes under stochastic resetting" (2025). Journal Articles. 5649.
https://digitalcommons.isical.ac.in/journal-articles/5649