Stochastic Search with Poisson and Deterministic Resetting

preprint2016arXivOpen access

Abstract

We investigate a stochastic search process in one, two, and three dimensions in which NN diffusing searchers that all start at x0x_0 seek a target at the origin. Each of the searchers is also reset to its starting point, either with rate rr, or deterministically, with a reset time TT. 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 NN, 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 NN searchers, including the search time being independent of TT for 1/T→01/T\to 0 and the search cost being independent of NN over a suitable range of NN. Moreover, deterministic resetting typically leads to a lower search cost than in stochastic resetting.

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