Publication :
Spectral dimension reduction of complex dynamical networks

ali.license-refhttps://creativecommons.org/licenses/by/4.0fr
ali.license-ref.start-date2020-01-17fr
bul.description.provenanceec spbfr
bul.rights.dateAccepPubl2019-03-04fr
bul.rights.periodeEmbargoP0Mfr
bul.rights.typeDatedatePublicationfr
dc.contributor.authorLaurence, Edward
dc.contributor.authorDubé, Louis J.
dc.contributor.authorDoyon, Nicolas
dc.contributor.authorDesrosiers, Patrick
dc.date.accessioned2020-01-20T15:49:33Z
dc.date.available2020-01-20T15:49:33Z
dc.date.issued2019-03-04
dc.description.abstractDynamical networks are powerful tools for modeling a broad range of complex systems, including financial markets, brains, and ecosystems. They encode how the basic elements (nodes) of these systems interact altogether (via links) and evolve (nodes’ dynamics). Despite substantial progress, little is known about why some subtle changes in the network structure, at the so-called critical points, can provoke drastic shifts in its dynamics. We tackle this challenging problem by introducing a method that reduces any network to a simplified low-dimensional version. It can then be used to describe the collective dynamics of the original system. This dimension reduction method relies on spectral graph theory and, more specifically, on the dominant eigenvalues and eigenvectors of the network adjacency matrix. Contrary to previous approaches, our method is able to predict the multiple activation of modular networks as well as the critical points of random networks with arbitrary degree distributions. Our results are of both fundamental and practical interest, as they offer a novel framework to relate the structure of networks to their dynamics and to study the resilience of complex systems.fr
dc.identifier.doi10.1103/PhysRevX.9.011042fr
dc.identifier.issn2160-3308fr
dc.identifier.urihttp://hdl.handle.net/20.500.11794/37847
dc.languageengfr
dc.publisherAmerican Physical Societyfr
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectComplex Systemsfr
dc.subjectNonlinear Dynamicsfr
dc.subjectStatistical Physicsfr
dc.subject.rvmSystèmes complexesfr
dc.subject.rvmSystèmes non linéairesfr
dc.subject.rvmPhysique statistiquefr
dc.titleSpectral dimension reduction of complex dynamical networksfr
dc.typearticle de recherche
dc.type.legacyCOAR1_1::Texte::Périodique::Revue::Contribution à un journal::Article::Article de recherchefr
dcterms.bibliographicCitationPhysical review x, Vol. 9 (1) (2019)fr
dspace.accessstatus.time2023-01-28 18:02:03
dspace.entity.typePublication
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rioxxterms.project.funder-nameFonds de Recherche du Québec - Nature et Technologiesfr
rioxxterms.project.funder-nameNatural Sciences and Engineering Research Council of Canadafr
rioxxterms.project.funder-nameSentinelle Nord, Université Lavalfr
rioxxterms.versionVoRfr
rioxxterms.version-of-recordhttps://doi.org/10.1103/PhysRevX.9.011042fr
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