Collective self-optimization of communicating active particles

Abstract

The quest on 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 unveiling aspects of the communication rules which certain social groups use to maximize their survival chances.

arXiv comment22 pages, 5 figures

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Cited by in corpus (7)

• The Parental Active Model: a unifying stochastic description of self-propulsion
• Role of rotational inertia for collective phenomena in active matter
• Stability of interlocked self-propelled dumbbell clusters
• Acoustic signaling enables collective perception and control in active matter systems
• AMEP: The Active Matter Evaluation Package for Python
• Collective dynamics and elasto-chemical cluster waves in communicating colloids with explicit size response
• Collective dynamics and shattering of disturbed two-dimensional Lennard-Jones crystals