Composite search of active particles in three-dimensional space based on non-directional cues

TL;DR

This paper investigates minimal, non-directional search strategies for active particles in 3D space to efficiently locate hidden targets, revealing how simple adaptive behaviors significantly improve search success.

Contribution

It introduces two novel composite search strategies that require minimal information processing and demonstrate substantial improvements in target encounter rates.

Findings

Optimal inner search time scales as a power-law with exponent -2/3.

Adaptive strategies exploit dynamic scattering effects to enhance search efficiency.

Minimal information strategies significantly increase target detection rates.

Abstract

We theoretically address minimal search strategies of active, self-propelled particles towards hidden targets in three-dimensional space. The particles can sense if a target is close, e.g., by detecting signaling molecules released by a target, but they cannot deduce any directional cues. We focus on composite search strategies, where particles switch between extensive outer search and intensive inner search; inner search is started when the proximity of a target is detected and ends again when a certain inner search time has elapsed. In the simplest strategy, active particles move ballistically during outer search, and transiently reduce their directional persistence during inner search. In a second, adaptive strategy, particles exploit a dynamic scattering effect by reducing directional persistence only outside a well-defined target zone. These two search strategies require only minimal information processing capabilities and a single binary or tertiary internal state, respectively, yet increases the rate of target encounter substantially. The optimal inner search time scales as a power-law with exponent -2/3 with target density, reflecting a trade-off between exploration and exploitation.