Information flow in finite flocks

We explore information flow in finite active matter flocks by simulating the canonical Vicsek model and estimating 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 flock...

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Detalles Bibliográficos
Autores principales: Brown, J., Bossomaier, T., Barnett, L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052242/
https://www.ncbi.nlm.nih.gov/pubmed/32123185
http://dx.doi.org/10.1038/s41598-020-59080-6
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author Brown, J.
Bossomaier, T.
Barnett, L.
author_facet Brown, J.
Bossomaier, T.
Barnett, L.
author_sort Brown, J.
collection PubMed
description We explore information flow in finite active matter flocks by simulating the canonical Vicsek model and estimating 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 throughout the entire ordered regime to very low noise values. This provides a foundation for future study regarding information flow in more complex models and real-world flocking data.
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spelling pubmed-70522422020-03-11 Information flow in finite flocks Brown, J. Bossomaier, T. Barnett, L. Sci Rep Article We explore information flow in finite active matter flocks by simulating the canonical Vicsek model and estimating 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 throughout the entire ordered regime to very low noise values. This provides a foundation for future study regarding information flow in more complex models and real-world flocking data. Nature Publishing Group UK 2020-03-02 /pmc/articles/PMC7052242/ /pubmed/32123185 http://dx.doi.org/10.1038/s41598-020-59080-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Brown, J.
Bossomaier, T.
Barnett, L.
Information flow in finite flocks
title Information flow in finite flocks
title_full Information flow in finite flocks
title_fullStr Information flow in finite flocks
title_full_unstemmed Information flow in finite flocks
title_short Information flow in finite flocks
title_sort information flow in finite flocks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052242/
https://www.ncbi.nlm.nih.gov/pubmed/32123185
http://dx.doi.org/10.1038/s41598-020-59080-6
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