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Keeping speed and distance for aligned motion.

Illés J Farkas1, Jeromos Kun2, Yi Jin3

  • 1MTA-ELTE Statistical and Biological Physics Research Group (Hungarian Academy of Sciences), Pázmány Péter sétány 1A, Budapest 1117, Hungary and Regional Knowledge Center, ELTE Faculty of Sciences, Irányi Dániel u. 4., Székesfehérvár 8000, Hungary.

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Summary
This summary is machine-generated.

Minimal models for collective motion are essential. Radial repulsion and self-propelling motion, without explicit velocity alignment, can generate flocking and swarming behavior in autonomous agents.

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Area of Science:

  • Physics
  • Complex Systems
  • Collective Behavior

Background:

  • Cohesive collective motion, such as flocking and swarming, is prevalent in nature and technology.
  • Minimal models are crucial for understanding the fundamental principles of collective motion.

Purpose of the Study:

  • To develop and analyze a minimal continuous-time model for collective motion.
  • To identify the essential components required for generating flocking and swarming behavior.

Main Methods:

  • A continuous space and time model was developed.
  • Microscopic rules included radial repulsion and linear self-propelling motion.
  • Simulations were conducted with varying particle densities, system sizes, and noise levels.

Main Results:

  • Radial repulsion and self-propelling motion are sufficient for flocking; explicit velocity alignment is not required.
  • Spatial confinement leads to stable macroscopic ordering.
  • A critical slowing down and discontinuous transition were observed with increasing noise, which becomes continuous in the infinite system limit.

Conclusions:

  • The proposed model offers a minimal yet effective description of flocking and swarming.
  • Velocity-based continuous models provide higher precision for asynchronous agents like animals and drones.
  • Optimal convergence to an ordered state occurs at finite particle density.