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dc.contributor.author
Barberis, Lucas Miguel
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dc.contributor.author
Peruani San Román, Fernando Miguel
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dc.date.available
2019-04-05T16:02:27Z
dc.date.issued
2016-12
dc.identifier.citation
Barberis, Lucas Miguel; Peruani San Román, Fernando Miguel; Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates; American Physical Society; Physical Review Letters; 117; 24; 12-2016; 1-6
dc.identifier.issn
0031-9007
dc.identifier.uri
http://hdl.handle.net/11336/73281
dc.description.abstract
We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit - due to the VC that breaks Newton´s third law - various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving - locally polar - files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Physical Society
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Self-Prpelled Particles
dc.subject
Cognitive Horizon
dc.subject
Action Reaction Breacking
dc.subject.classification
Astronomía
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dc.subject.classification
Ciencias Físicas
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-03-21T14:09:20Z
dc.journal.volume
117
dc.journal.number
24
dc.journal.pagination
1-6
dc.journal.pais
Estados Unidos
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dc.description.fil
Fil: Barberis, Lucas Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina
dc.description.fil
Fil: Peruani San Román, Fernando Miguel. Observatoire de la Cote D'Azur; Francia
dc.journal.title
Physical Review Letters
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1103/PhysRevLett.117.248001
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.117.248001
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