0000000000073406

AUTHOR

Alberto Robledo

showing 3 related works from this author

Entropy and Renormalization in Chaotic Visibility Graphs

2016

PhysicsCombinatoricsRenormalizationNonlinear time series analysisGraph entropy0103 physical sciencesChaoticEntropy (information theory)Statistical physics010306 general physics01 natural sciences010305 fluids & plasmas
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Feigenbaum graphs: a complex network perspective of chaos

2011

The recently formulated theory of horizontal visibility graphs transforms time series into graphs and allows the possibility of studying dynamical systems through the characterization of their associated networks. This method leads to a natural graph-theoretical description of nonlinear systems with qualities in the spirit of symbolic dynamics. We support our claim via the case study of the period-doubling and band-splitting attractor cascades that characterize unimodal maps. We provide a universal analytical description of this classic scenario in terms of the horizontal visibility graphs associated with the dynamics within the attractors, that we call Feigenbaum graphs, independent of map…

Dynamical systems theoryScienceSymbolic dynamicsFOS: Physical sciencesLyapunov exponentFixed pointBioinformatics01 natural sciences010305 fluids & plasmasStatistical Mechanicssymbols.namesake0103 physical sciencesAttractorEntropy (information theory)Statistical physics010306 general physicsChaotic SystemsCondensed-Matter PhysicsCondensed Matter - Statistical MechanicsPhysicsMultidisciplinaryStatistical Mechanics (cond-mat.stat-mech)Applied MathematicsPhysicsQRComplex SystemsComplex networkNonlinear Sciences - Chaotic DynamicsDegree distributionNonlinear DynamicssymbolsMedicineChaotic Dynamics (nlin.CD)MathematicsAlgorithmsResearch Article
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Analytical properties of horizontal visibility graphs in the Feigenbaum scenario

2012

Time series are proficiently converted into graphs via the horizontal visibility (HV) algorithm, which prompts interest in its capability for capturing the nature of different classes of series in a network context. We have recently shown [1] that dynamical systems can be studied from a novel perspective via the use of this method. Specifically, the period-doubling and band-splitting attractor cascades that characterize unimodal maps transform into families of graphs that turn out to be independent of map nonlinearity or other particulars. Here we provide an in depth description of the HV treatment of the Feigenbaum scenario, together with analytical derivations that relate to the degree di…

Dynamical systems theoryMatemáticasGeneral Physics and AstronomyFOS: Physical sciencesLyapunov exponentDynamical Systems (math.DS)Fixed point01 natural sciencesAeronáutica010305 fluids & plasmassymbols.namesakeBifurcation theoryOscillometry0103 physical sciencesAttractorFOS: MathematicsEntropy (information theory)Computer SimulationStatistical physicsMathematics - Dynamical Systems010306 general physicsMathematical PhysicsMathematicsSeries (mathematics)Degree (graph theory)Applied MathematicsStatistical and Nonlinear Physics16. Peace & justiceNonlinear Sciences - Chaotic DynamicsNonlinear DynamicsPhysics - Data Analysis Statistics and ProbabilitysymbolsChaotic Dynamics (nlin.CD)AlgorithmsData Analysis Statistics and Probability (physics.data-an)
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