A Hitchhiker’s Guide to Active Motion
Author Information
Author(s): Tobias Plasczyk, Paul A. Monderkamp, Hartmut Löwen, René Wittmann
Primary Institution: Heinrich-Heine-Universität Düsseldorf
Hypothesis
Can a motorless particle effectively navigate by hitchhiking on active Brownian particles?
Conclusion
The intelligent hitchhiking particle (IHP) can outperform bath particles in long-time ballistic motion by learning to attach to favorable active particles.
Supporting Evidence
- The IHP learns to navigate by attaching to active particles with favorable orientations.
- The study demonstrates that the IHP can anticipate the motion patterns of its hosts.
- The performance of the IHP improves with training cycles, showing effective learning.
- The IHP's strategy can be transferred to systems with different interaction potentials.
Takeaway
This study shows how a particle that can't move on its own can learn to ride on other moving particles to get where it wants to go, like hitchhiking.
Methodology
The study uses a reinforcement learning algorithm to model the behavior of an intelligent hitchhiking particle in a bath of active Brownian particles.
Limitations
The model assumes non-reciprocal interactions and does not account for the effects of the IHP on the bath particles.
Digital Object Identifier (DOI)
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