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  • Open Access

Optimal Area Exploration by Resetting Active Particles

Kristian Stølevik Olsen1,*, Hartmut Löwen1, and Lorenzo Caprini2,†

  • *Contact author: kristian.olsen@hhu.de
  • †Contact author: lorenzo.caprini@uniroma1.it
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Phys. Rev. Lett. 137, 057102 – Published 28 July, 2026

DOI: https://doi.org/10.1103/sytg-m4ms

Abstract

Identifying optimal strategies for efficient spatial exploration is crucial, both for animals seeking food and for robotic search processes, where maximizing the explored area is a fundamental requirement. Here, we propose position resetting as an optimal protocol to enhance spatial exploration in active matter systems. Specifically, we show that the area covered by an active Brownian particle depends nonmonotonically on the resetting rate, demonstrating that resetting can optimize spatial exploration. Our results are based on experiments with active granular particles undergoing Poissonian resetting and are supported by simulations of active Brownian dynamics. The covered area is analytically predicted for both large and small resetting rates, leading to a scaling relation between the optimal resetting rate and the self-propulsion speed.

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Phys. Rev. Lett. 137, 057102– Published 28 July, 2026
  • Received 30 August 2024
  • Accepted 29 June 2026
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