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In many situations, simply finding a target during a search is not enough. It is equally important to be able to return to that target repeatedly or to enable a larger community to locate and utilize it. While first passage time is commonly used to measure search success, relatively little is known about measures of repeated target encounters, such as the mean first passage count (MFPC), and their rate over time. Here we compare an active Brownian particle model with central resetting, with and without chemotaxis. Searchers with no individual memory but shared environmental memory encode information about the target's location in the environment, outperforming purely memoryless strategies by boosting the overall hit rate. We further show that this approach leads to a sublinear dependence of encounter rate on target size, reducing the impact of target size on a successful search and increasing the total utilization time of the target.
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Rudyak et al. (2026) studied this question.
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