Spatio-temporal correlations in models of collective motion ruled by different dynamical laws
- Autores
- Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomás Sebastián; Melillo, Stefania; Viale, Massimiliano
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Information transfer is an essential factor in determining the robustness of collective behaviour in biological systems with distributed control. The most direct way to study the information transfer mechanisms is to experimentally detect the propagation across the system of a signal triggered by some perturbation. However, for field experiments this method is inefficient, as the possibilities of the observer to perturb the group are limited and empirical observations must rely on rare natural perturbations. An alternative way is to use spatio-temporal correlations to assess the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. We test the approach on ground truth data provided by numerical simulations in three dimensions of two models of collective behaviour characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an un- derdamped inertial dynamics. By using dynamical finite size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.
Instituto de Física de Líquidos y Sistemas Biológicos - Materia
-
Física
Biología
Biological physics
Information transfer
Statistical mechanics
Collective behavior
Spatio-temporal correlations - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/129616
Ver los metadatos del registro completo
id |
SEDICI_1a3a5dec93fb36c0b6a179228db44237 |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/129616 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
network_name_str |
SEDICI (UNLP) |
spelling |
Spatio-temporal correlations in models of collective motion ruled by different dynamical lawsCavagna, AndreaConti, DanieleGiardina, IreneGrigera, Tomás SebastiánMelillo, StefaniaViale, MassimilianoFísicaBiologíaBiological physicsInformation transferStatistical mechanicsCollective behaviorSpatio-temporal correlationsInformation transfer is an essential factor in determining the robustness of collective behaviour in biological systems with distributed control. The most direct way to study the information transfer mechanisms is to experimentally detect the propagation across the system of a signal triggered by some perturbation. However, for field experiments this method is inefficient, as the possibilities of the observer to perturb the group are limited and empirical observations must rely on rare natural perturbations. An alternative way is to use spatio-temporal correlations to assess the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. We test the approach on ground truth data provided by numerical simulations in three dimensions of two models of collective behaviour characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an un- derdamped inertial dynamics. By using dynamical finite size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.Instituto de Física de Líquidos y Sistemas Biológicos2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/129616enginfo:eu-repo/semantics/altIdentifier/issn/1478-3975info:eu-repo/semantics/altIdentifier/issn/1478-3967info:eu-repo/semantics/altIdentifier/arxiv/1605.09628info:eu-repo/semantics/altIdentifier/pmid/27845926info:eu-repo/semantics/altIdentifier/doi/10.1088/1478-3975/13/6/065001info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:31:17Zoai:sedici.unlp.edu.ar:10915/129616Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:31:17.667SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
spellingShingle |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws Cavagna, Andrea Física Biología Biological physics Information transfer Statistical mechanics Collective behavior Spatio-temporal correlations |
title_short |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_full |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_fullStr |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_full_unstemmed |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
title_sort |
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws |
dc.creator.none.fl_str_mv |
Cavagna, Andrea Conti, Daniele Giardina, Irene Grigera, Tomás Sebastián Melillo, Stefania Viale, Massimiliano |
author |
Cavagna, Andrea |
author_facet |
Cavagna, Andrea Conti, Daniele Giardina, Irene Grigera, Tomás Sebastián Melillo, Stefania Viale, Massimiliano |
author_role |
author |
author2 |
Conti, Daniele Giardina, Irene Grigera, Tomás Sebastián Melillo, Stefania Viale, Massimiliano |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Física Biología Biological physics Information transfer Statistical mechanics Collective behavior Spatio-temporal correlations |
topic |
Física Biología Biological physics Information transfer Statistical mechanics Collective behavior Spatio-temporal correlations |
dc.description.none.fl_txt_mv |
Information transfer is an essential factor in determining the robustness of collective behaviour in biological systems with distributed control. The most direct way to study the information transfer mechanisms is to experimentally detect the propagation across the system of a signal triggered by some perturbation. However, for field experiments this method is inefficient, as the possibilities of the observer to perturb the group are limited and empirical observations must rely on rare natural perturbations. An alternative way is to use spatio-temporal correlations to assess the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. We test the approach on ground truth data provided by numerical simulations in three dimensions of two models of collective behaviour characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an un- derdamped inertial dynamics. By using dynamical finite size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model. Instituto de Física de Líquidos y Sistemas Biológicos |
description |
Information transfer is an essential factor in determining the robustness of collective behaviour in biological systems with distributed control. The most direct way to study the information transfer mechanisms is to experimentally detect the propagation across the system of a signal triggered by some perturbation. However, for field experiments this method is inefficient, as the possibilities of the observer to perturb the group are limited and empirical observations must rely on rare natural perturbations. An alternative way is to use spatio-temporal correlations to assess the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. We test the approach on ground truth data provided by numerical simulations in three dimensions of two models of collective behaviour characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an un- derdamped inertial dynamics. By using dynamical finite size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/129616 |
url |
http://sedici.unlp.edu.ar/handle/10915/129616 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/1478-3975 info:eu-repo/semantics/altIdentifier/issn/1478-3967 info:eu-repo/semantics/altIdentifier/arxiv/1605.09628 info:eu-repo/semantics/altIdentifier/pmid/27845926 info:eu-repo/semantics/altIdentifier/doi/10.1088/1478-3975/13/6/065001 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
reponame_str |
SEDICI (UNLP) |
collection |
SEDICI (UNLP) |
instname_str |
Universidad Nacional de La Plata |
instacron_str |
UNLP |
institution |
UNLP |
repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
_version_ |
1844616192447217664 |
score |
13.070432 |