Autor según el artículo: De Domenico, M.
Departamento: Enginyeria Informàtica i Matemàtiques
Autor/es de la URV: DE DOMENICO ., MANLIO
Palabras clave: Dynamics diffusion Biological systems
Resumen: Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.
Grupo de investigación: Algorithms embedded in Physical Systems
Áreas temáticas: Computer engineering Ingeniería informática Enginyeria informàtica
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 0031-9007
Identificador del autor: 0000-0001-5158-8594
Fecha de alta del registro: 2017-05-17
Volumen de revista: 118
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
Enlace a la fuente original: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.118.168301
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
DOI del artículo: 10.1103/PhysRevLett.118.168301
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2017
Página inicial: Art.num.168301
Tipo de publicación: Article Artículo Article
Repositori URV