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How environment affects active particle swarms: a case study

We investigate the collective motion of self-propelled agents in an environment filled with obstacles that are tethered to fixed positions via springs. The active particles are able to modify the environment by moving the obstacles through repulsion forces. This creates feedback interactions between...

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Autores principales: Degond, Pierre, Manhart, Angelika, Merino-Aceituno, Sara, Peurichard, Diane, Sala, Lorenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748504/
https://www.ncbi.nlm.nih.gov/pubmed/36533200
http://dx.doi.org/10.1098/rsos.220791
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author Degond, Pierre
Manhart, Angelika
Merino-Aceituno, Sara
Peurichard, Diane
Sala, Lorenzo
author_facet Degond, Pierre
Manhart, Angelika
Merino-Aceituno, Sara
Peurichard, Diane
Sala, Lorenzo
author_sort Degond, Pierre
collection PubMed
description We investigate the collective motion of self-propelled agents in an environment filled with obstacles that are tethered to fixed positions via springs. The active particles are able to modify the environment by moving the obstacles through repulsion forces. This creates feedback interactions between the particles and the obstacles from which a breadth of patterns emerges (trails, band, clusters, honey-comb structures, etc.). We will focus on a discrete model first introduced in Aceves-Sanchez P et al. (2020, Bull. Math. Biol. 82, 125 (doi:10.1007/s11538-020-00805-z)), and derived into a continuum PDE model. As a first major novelty, we perform an in-depth investigation of pattern formation of the discrete and continuum models in two dimensions: we provide phase-diagrams and determine the key mechanisms for bifurcations to happen using linear stability analysis. As a result, we discover that the agent-agent repulsion, the agent-obstacle repulsion and the obstacle’s spring stiffness are the key forces in the appearance of patterns, while alignment forces between the particles play a secondary role. The second major novelty lies in the development of an innovative methodology to compare discrete and continuum models that we apply here to perform an in-depth analysis of the agreement between the discrete and continuum models.
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spelling pubmed-97485042022-12-16 How environment affects active particle swarms: a case study Degond, Pierre Manhart, Angelika Merino-Aceituno, Sara Peurichard, Diane Sala, Lorenzo R Soc Open Sci Mathematics We investigate the collective motion of self-propelled agents in an environment filled with obstacles that are tethered to fixed positions via springs. The active particles are able to modify the environment by moving the obstacles through repulsion forces. This creates feedback interactions between the particles and the obstacles from which a breadth of patterns emerges (trails, band, clusters, honey-comb structures, etc.). We will focus on a discrete model first introduced in Aceves-Sanchez P et al. (2020, Bull. Math. Biol. 82, 125 (doi:10.1007/s11538-020-00805-z)), and derived into a continuum PDE model. As a first major novelty, we perform an in-depth investigation of pattern formation of the discrete and continuum models in two dimensions: we provide phase-diagrams and determine the key mechanisms for bifurcations to happen using linear stability analysis. As a result, we discover that the agent-agent repulsion, the agent-obstacle repulsion and the obstacle’s spring stiffness are the key forces in the appearance of patterns, while alignment forces between the particles play a secondary role. The second major novelty lies in the development of an innovative methodology to compare discrete and continuum models that we apply here to perform an in-depth analysis of the agreement between the discrete and continuum models. The Royal Society 2022-12-14 /pmc/articles/PMC9748504/ /pubmed/36533200 http://dx.doi.org/10.1098/rsos.220791 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Mathematics
Degond, Pierre
Manhart, Angelika
Merino-Aceituno, Sara
Peurichard, Diane
Sala, Lorenzo
How environment affects active particle swarms: a case study
title How environment affects active particle swarms: a case study
title_full How environment affects active particle swarms: a case study
title_fullStr How environment affects active particle swarms: a case study
title_full_unstemmed How environment affects active particle swarms: a case study
title_short How environment affects active particle swarms: a case study
title_sort how environment affects active particle swarms: a case study
topic Mathematics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748504/
https://www.ncbi.nlm.nih.gov/pubmed/36533200
http://dx.doi.org/10.1098/rsos.220791
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