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Optimal navigation strategy of active Brownian particles in target-search problems
Luigi Zanovello1, Pietro Faccioli2, Thomas Franosch1
1Institut für Theoretische Physik, Universität Innsbruck, Technikerstraße 21A, A-6020 Innsbruck, Austria.
Active Brownian particles, or microswimmers, can improve target finding by adjusting their movement based on the environment. Their search patterns are robust, unlike passive particles, even with complex landscapes.
Area of Science:
- Physics
- Biophysics
- Statistical Mechanics
Background:
- Microswimmers are model systems for exploring complex environments.
- Active Brownian particles exhibit unique search strategies.
- Understanding target localization in energy landscapes is crucial.
Purpose of the Study:
- To investigate the exploration patterns of microswimmers in energy landscapes.
- To determine how microswimmers find targets separated by high energy barriers.
- To analyze the role of activity and persistence in search efficiency.
Main Methods:
- Modeling microswimmers as active Brownian particles.
- Simulating search dynamics in a potential energy landscape.
- Analyzing target-search patterns, transition rates, and path times.
Main Results:
- Microswimmers enhance target search success by tuning activity and persistence.
- Search patterns are robust to energy landscape variations.
- Transition dynamics are sensitive to landscape details but not significantly slowed by local minima.
Conclusions:
- Active Brownian particle dynamics offer efficient target localization strategies.
- Environmental adaptation is key for microswimmer search success.
- Active search is resilient to landscape complexity compared to passive systems.
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