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.
Authors
- Leonardo Dagdug (ORCID: https://orcid.org/0000-0002-2654-9267)
- Dibakar Ghosh (ORCID: https://orcid.org/0000-0003-4832-5210)
- A. Pal (ORCID: https://orcid.org/0000-0001-6806-5431)
- Denis Boyer (ORCID: https://orcid.org/0000-0003-2676-6752)
- Suvam Pal (ORCID: https://orcid.org/0009-0002-1979-1378)
Institutions
- Homi Bhabha National Institute (IN)
- Universidad Autónoma Metropolitana (MX)
- Institute of Mathematical Sciences (IN)
- Indian Statistical Institute (IN)
- Universidad Nacional Autónoma de México (MX)
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