Berlin 2018 – scientific programme
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DY: Fachverband Dynamik und Statistische Physik
DY 67: Poster: Active Matter, Microswimmers
DY 67.7: Poster
Thursday, March 15, 2018, 15:30–18:00, Poster A
Discriminating collective motion mechanisms using correlations and information measures — •Yinong Zhao1, Zhangang Han2, Pawel Romanczuk1, and Cristian Huepe2, 3, 4 — 1ITB, Humboldt-Universität zu Berlin, 10115 Berlin, Germany — 2School of Systems Science, Beijing Normal University, Beijing 100875, China — 3CHuepe Labs, 954 West 18th Place, Chicago, IL 60608, USA — 4Northwestern Institute on Complex Systems and ESAM, Northwestern University, Evanston, IL 60208, USA
Collective motion is an emergent phenomenon observed in a variety of living systems. Although a variety of models have been introduced that can achieve collective motion in the presence of noise, it is still unclear which, if any, of these algorithms is followed by different animal groups.
We consider different measures that use individual heading and are based on correlations and information theory. We show that these measures can discriminate among various minimal models of collective motion. The models include different types of interactions, either metric or topological and based on either relative heading angles or positions. We show that under a high-noise environment, position-based model shows better collective performance than velocity-based model.
Given their ability to discriminate between different simple models, these measures could be used to help infer the underlying mechanism that leads to collective motion in different experimental systems.