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Swarm dynamics of delayed self-propelled particles with non-reciprocal interactions

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  • Zhou, Yongjian
  • Zheng, Zhicheng
  • Wang, Tao
  • Peng, Xingguang

Abstract

Non-reciprocal interactions are prevalent in various natural systems such as neuronal networks and predator–prey dynamics, sparking significant interest in recent research. This study delves into the impact of non-reciprocal interactions on collective behavior using a model of delayed self-propelled particles with purely attraction. Our investigation reveals a variety of states that emerge within this dynamical framework: ring state, rotating state, and especially translating state that emerge spontaneously in the absence of velocity alignment. Additionally, all states exhibit segregation due to these non-reciprocal interactions. We employ mean field approximation and bifurcation analysis techniques to analyze the boundaries and characteristics of these states in parameter space. Furthermore, we validate our theoretical findings through numerical simulations.

Suggested Citation

  • Zhou, Yongjian & Zheng, Zhicheng & Wang, Tao & Peng, Xingguang, 2024. "Swarm dynamics of delayed self-propelled particles with non-reciprocal interactions," Chaos, Solitons & Fractals, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:chsofr:v:186:y:2024:i:c:s0960077924008543
    DOI: 10.1016/j.chaos.2024.115302
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    References listed on IDEAS

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    3. Vincent Ouazan-Reboul & Jaime Agudo-Canalejo & Ramin Golestanian, 2023. "Self-organization of primitive metabolic cycles due to non-reciprocal interactions," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    4. Zhou, Yongjian & Wang, Tonghao & Lei, Xiaokang & Peng, Xingguang, 2024. "Collective behavior of self-propelled particles with heterogeneity in both dynamics and delays," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
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