Predator-prey dynamics: Chasing by stochastic resetting

Predator-prey dynamics: Chasing by stochastic resetting

We analyze predator-prey dynamics in one dimension in which a Brownian predator adopts a chasing strategy that consists in stochastically resetting its current position to locations previously visited by a diffusive prey. We study three different chasing strategies, namely, active, uniform and passi...

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Hauptverfasser: Toledo-Marin, J. Quetzalcoatl, Boyer, Denis, Sevilla, Francisco J
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Physics - Disordered Systems and Neural Networks
Physics - Statistical Mechanics
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Boyer, Denis
Sevilla, Francisco J
description We analyze predator-prey dynamics in one dimension in which a Brownian predator adopts a chasing strategy that consists in stochastically resetting its current position to locations previously visited by a diffusive prey. We study three different chasing strategies, namely, active, uniform and passive which lead to different diffusive behaviors of the predator in the absence of capture. When capture is considered, regardless of the chasing strategy, the mean first-encounter time is finite and decreases with the resetting rate. This model illustrates how the use of cues significantly improves the efficiency of random searches. We compare numerical simulations with analytical calculations and find excellent agreement.
doi_str_mv 10.48550/arxiv.1912.02141
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Physics - Statistical Mechanics
title Predator-prey dynamics: Chasing by stochastic resetting
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