Effects of local population structure in a reaction-diffusion model of a contact process on metapopulation networks

We investigate the effects of local population structure in reaction-diffusion processes representing a contact process (CP) on metapopulations represented as complex networks. Considering a model in which the nodes of a large scale network represent local populations defined in terms of a homogeneo...

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Detalhes bibliográficos
Autores: Mata, Angélica S., Ferreira, Silvio C., Pastor-Satorras, Romualdo
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2013
País:Brasil
Recursos:Universidade Federal de Viçosa (UFV)
Repositório:LOCUS Repositório Institucional da UFV
Idioma:inglês
OAI Identifier:oai:locus.ufv.br:123456789/13032
Acesso em linha:https://doi.org/10.1103/PhysRevE.88.042820
http://www.locus.ufv.br/handle/123456789/13032
Access Level:Acceso aberto
Palavra-chave:Effects of local population structure
Reaction-diffusion model
Metapopulation networks
Descrição
Resumo:We investigate the effects of local population structure in reaction-diffusion processes representing a contact process (CP) on metapopulations represented as complex networks. Considering a model in which the nodes of a large scale network represent local populations defined in terms of a homogeneous graph, we show by means of extensive numerical simulations that the critical properties of the reaction-diffusion system are independent of the local population structure, even when this one is given by a ordered linear chain. This independence is confirmed by the perfect matching between numerical critical exponents and the results from a heterogeneous mean-field theory suited, in principle, to describe situations of local homogeneous mixing. The analysis of several variations of the reaction-diffusion process allows us to conclude the independence from population structure of the critical properties of CP-like models on metapopulations, and thus of the universality of the reaction-diffusion description of this kind of models.