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Horizontal visibility graphs generated by type-I intermittency.
Núñez, Ángel M; Luque, Bartolo; Lacasa, Lucas; Gómez, Jose Patricio; Robledo, Alberto.
Afiliação
  • Núñez ÁM; Dept. Matemática Aplicada y Estadística, ETSI Aeronáuticos, Universidad Politécnica de Madrid, Madrid, Spain.
Article em En | MEDLINE | ID: mdl-23767578
ABSTRACT
The type-I intermittency route to (or out of) chaos is investigated within the horizontal visibility (HV) graph theory. For that purpose, we address the trajectories generated by unimodal maps close to an inverse tangent bifurcation and construct their associated HV graphs. We show how the alternation of laminar episodes and chaotic bursts imprints a fingerprint in the resulting graph structure. Accordingly, we derive a phenomenological theory that predicts quantitative values for several network parameters. In particular, we predict that the characteristic power-law scaling of the mean length of laminar trend sizes is fully inherited by the variance of the graph degree distribution, in good agreement with the numerics. We also report numerical evidence on how the characteristic power-law scaling of the Lyapunov exponent as a function of the distance to the tangent bifurcation is inherited in the graph by an analogous scaling of block entropy functionals defined on the graph. Furthermore, we are able to recast the full set of HV graphs generated by intermittent dynamics into a renormalization-group framework, where the fixed points of its graph-theoretical renormalization-group flow account for the different types of dynamics. We also establish that the nontrivial fixed point of this flow coincides with the tangency condition and that the corresponding invariant graph exhibits extremal entropic properties.
Assuntos
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Base de dados: MEDLINE Assunto principal: Algoritmos / Gráficos por Computador / Análise Numérica Assistida por Computador / Modelos Estatísticos / Dinâmica não Linear Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Ano de publicação: 2013 Tipo de documento: Article
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Base de dados: MEDLINE Assunto principal: Algoritmos / Gráficos por Computador / Análise Numérica Assistida por Computador / Modelos Estatísticos / Dinâmica não Linear Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Ano de publicação: 2013 Tipo de documento: Article