2018/05/31 by Trilochan Bagarti, Shakti N. Menon · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Acoustics #Classical mechanics #Computer science #Diffusion and Search Dynamics #Distributed Control Multi-Agent Systems #Dynamics (music) #Flocking (texture) #Geology #Mechanics #Micro and Nano Robotics #Physics #Statistical physics #cond-mat.stat-mech #nlin.AO
paper · pdf · doi:10.1103/physreve.100.012609
published as Phys. Rev. E 100, 012609 (2019) · 5 pages, 3 figures + 9 pages supplementary material; added text to Fig. 1, fixed normalization in Fig. 2, revised Fig. 3, minor revisions to the main text, additional references included, new section added to SI
arxiv created 2018/10/20 · openalex publication_date 2019/07/19 · arxiv updated 2019/07/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We introduce a stochastic agent-based model for the flocking dynamics of self-propelled particles that exhibit nonlinear velocity-alignment interactions with neighbors within their field of view. The stochasticity in the dynamics is spatially heterogeneous and arises implicitly from the nature of the interparticle interactions. We observe long-time spatial cohesion in the emergent flocking dynamics, despite the absence of attractive forces that explicitly depend on the relative positions of particles. The wide array of flocking patterns exhibited by this model are characterized by identifying spatially distinct clusters and computing their corresponding angular momenta.