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  Collective self-optimization of communicating active particles

Zampetaki, A., Liebchen, B., Ivlev, A. V., & Löwen, H. (2021). Collective self-optimization of communicating active particles. Proceedings of the National Academy of Sciences of the United States of America, 118(49): e2111142118. doi:10.1073/pnas.2111142118.

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Zampetaki, Alexandra1, Author           
Liebchen, Benno, Author
Ivlev, Alexej V.1, Author           
Löwen, Hartmut, Author
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1Center for Astrochemical Studies at MPE, MPI for Extraterrestrial Physics, Max Planck Society, ou_1950287              

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 Abstract: The quest for how to collectively self-organize in order to maximize the survival chances of the members of a social group requires finding an optimal compromise between maximizing the well-being of an individual and that of the group. Here we develop a minimal model describing active individuals which consume or produce, and respond to a shared resource—such as the oxygen concentration for aerotactic bacteria or the temperature field for penguins—while urging for an optimal resource value. Notably, this model can be approximated by an attraction–repulsion model, but, in general, it features many-body interactions. While the former prevents some individuals from closely approaching the optimal value of the shared “resource field,” the collective many-body interactions induce aperiodic patterns, allowing the group to collectively self-optimize. Arguably, the proposed optimal field–based collective interactions represent a generic concept at the interface of active matter physics, collective behavior, and microbiological chemotaxis. This concept might serve as a useful ingredient to optimize ensembles of synthetic active agents or to help unveil aspects of the communication rules which certain social groups use to maximize their survival chances.

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Language(s): eng - English
 Dates: 2021-12-01
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.1073/pnas.2111142118
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Title: Proceedings of the National Academy of Sciences of the United States of America
  Other : Proc. Natl. Acad. Sci. U. S. A.
Source Genre: Journal
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Publ. Info: National Academy of Sciences
Pages: - Volume / Issue: 118 (49) Sequence Number: e2111142118 Start / End Page: - Identifier: ISSN: 0027-8424