Stochastic Search with Poisson and Deterministic Resetting
Abstract
We investigate a stochastic search process in one, two, and three dimensions in which diffusing searchers that all start at seek a target at the origin. Each of the searchers is also reset to its starting point, either with rate , or deterministically, with a reset time . In one dimension and for a small number of searchers, the search time and the search cost are minimized at a non-zero optimal reset rate (or time), while for sufficiently large , resetting always hinders the search. In general, a single searcher leads to the minimum search cost in one, two, and three dimensions. When the resetting is deterministic, several unexpected feature arise for searchers, including the search time being independent of for and the search cost being independent of over a suitable range of . Moreover, deterministic resetting typically leads to a lower search cost than in stochastic resetting.
Keywords
Cite
@article{arxiv.1605.08812,
title = {Stochastic Search with Poisson and Deterministic Resetting},
author = {Uttam Bhat and Caterina De Bacco and S. Redner},
journal= {arXiv preprint arXiv:1605.08812},
year = {2016}
}
Comments
23 pages, 9 figures, IOP format. Revised version: figure added, introductory text added, references added, and various minor changes incorporated. V3: Final version to appear in JSTAT. A few more references added