2014/11/30 by Ruben van Drongelen, Arup Kumar Pal, Anshuman Pal +2 · 1 citation
Biochemistry, Genetics and Molecular Biology · Engineering · Mathematics · Physics and Astronomy · #Acoustics #Artificial intelligence #Biological system #Biology #Boundary (topology) #Boundary value problem #Classical mechanics #Collective behavior #Collective motion #Computer science #Constant (computer programming) #Diffusion #Diffusion and Search Dynamics #Dynamics (music) #Ecology #Fick's laws of diffusion #Materials science #Mathematical analysis #Mathematics #Micro and Nano Robotics #Molecular Communication and Nanonetworks #Motion (physics) #Particle (ecology) #Periodic boundary conditions #Physics #Range (aeronautics) #Statistical physics #Swarm behaviour #cond-mat.soft #physics.bio-ph
paper · pdf · doi:10.1103/physreve.91.032706
published as Phys. Rev. E 91, 032706 (2015) · 8 pages, 7 figures
openalex publication_date 2015/03/13 · arxiv created 2016/10/12 · arxiv updated 2016/10/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We present a model of soft active particles that leads to a rich array of collective behavior found also in dense biological swarms of bacteria and other unicellular organisms. Our model uses only local interactions, such as Vicsek-type nearest-neighbor alignment, short-range repulsion, and a local boundary term. Changing the relative strength of these interactions leads to migrating swarms, rotating swarms, and jammed swarms, as well as swarms that exhibit run-and-tumble motion, alternating between migration and either rotating or jammed states. Interestingly, although a migrating swarm moves slower than an individual particle, the diffusion constant can be up to three orders of magnitude larger, suggesting that collective motion can be highly advantageous, for example, when searching for food.