Identifying complex periodic windows in continuous-time dynamical systems using recurrence-based methods

Yong  Zou; Reik V.  Donner; Jonathan F.  Donges; Norbert  Marwan; Jürgen  Kurths

doi:10.1063/1.3523304

ABSTRACT

The identification of complex periodic windows in the two-dimensional parameter space of certain dynamical systems has recently attracted considerable interest. While for discrete systems, a discrimination between periodic and chaotic windows can be easily made based on the maximum Lyapunov exponent of the system, this remains a challenging task for continuous systems, especially if only short time series are available (e.g., in case of experimental data). In this work, we demonstrate that nonlinear measures based on recurrence plots obtained from such trajectories provide a practicable alternative for numerically detecting shrimps. Traditional diagonal line-based measures of recurrence quantification analysis as well as measures from complex network theory are shown to allow an excellent classification of periodic and chaotic behavior in parameter space. Using the well-studied Rössler system as a benchmark example, we find that the average path length and the clustering coefficient of the resulting recurrence networks are particularly powerful discriminatory statistics for the identification of complex periodic windows.

ACKNOWLEDGMENTS

This work has been financially supported by the German Research Foundation (DFG) (Project No. He 2789/8-2), the Max Planck Society, the Federal Ministry for Education and Research (BMBF) via the Potsdam Research Cluster for Georisk Analysis, Environmental Change and Sustainability (PROGRESS), and the Leibniz association (project ECONS). All complex network measures have been calculated using the software package IGRAPH.⁶⁶66. G. Csárdi and T. Nepusz, InterJournal CX.18, 1695 (2006). We thank K. Kramer for help with the IBM iDataPlex Cluster at the Potsdam Institute for Climate Impact Research, on which all calculations were performed.

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Identifying complex periodic windows in continuous-time dynamical systems using recurrence-based methods

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