Information flow in finite flocks
| Autor: | Lionel Barnett, Terry Bossomaier, Joshua Brown |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Phase transition
Multidisciplinary Statistical Mechanics (cond-mat.stat-mech) Flocking (behavior) lcsh:R Complex networks FOS: Physical sciences lcsh:Medicine 01 natural sciences Article 010305 fluids & plasmas Active matter Low noise 0103 physical sciences Information theory and computation lcsh:Q Transfer entropy Ising model Information flow (information theory) Flock Statistical physics lcsh:Science 010306 general physics Condensed Matter - Statistical Mechanics Mathematics |
| Zdroj: | Scientific Reports, Vol 10, Iss 1, Pp 1-8 (2020) Scientific Reports |
| ISSN: | 2045-2322 |
| Popis: | We simulate the canonical Vicsek model and estimate the flow of information as a function of noise (the variability in the extent to which each animal aligns with its neighbours). We show that the global transfer entropy for finite flocks not only fails to peak near the phase transition, as demonstrated for the canonical 2D Ising model, but remains constant from the transition to very low noise values. This provides a foundation for future study regarding information flow in more complex models and real-world flocking data. 10 pages, 6 figures, 1 ancillary file (supplemental materials) |
| Databáze: | OpenAIRE |
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