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A classification scheme for chimera states.
Felix P Kemeth1, Sindre W Haugland1, Lennart Schmidt1
1Physik-Department, Nonequilibrium Chemical Physics, Technische Universität München, James-Franck-Str. 1, D-85748 Garching, Germany.
Chaos (Woodbury, N.Y.)
|October 27, 2016
Summary
We developed a universal method to characterize chimera states using two correlation measures. This allows for consistent classification of stationary, turbulent, and breathing chimera states in numerical and experimental data.
Area of Science:
- Complex systems
- Nonlinear dynamics
- Network science
Background:
- Chimera states, a unique phenomenon in coupled oscillator systems, exhibit coexisting domains of synchronized and desynchronized behavior.
- Previous characterization methods lacked universality, hindering direct comparison between numerical simulations and experimental findings.
- The precise classification and quantification of chimera states remain challenging.
Purpose of the Study:
- To introduce a universal characterization scheme for chimera states.
- To enable meaningful definition and classification of chimera states.
- To facilitate quantitative comparisons between numerical and experimental chimera states.
Main Methods:
- Development of a scheme based on two correlation measures.
- Application of the scheme to both numerical and experimental datasets.
- Classification into stationary, turbulent, and breathing categories, with further subdivisions based on time-stationarity.
Main Results:
- The proposed scheme provides a consistent definition and classification of chimera states.
- Identified and categorized previously uncategorized chimera states.
- Enabled qualitative and quantitative comparisons between simulated and experimental chimera states.
Conclusions:
- The universal characterization scheme offers a robust framework for studying chimera states.
- This approach enhances the understanding and comparability of chimera phenomena across different systems.
- The scheme bridges the gap between theoretical models and empirical observations in complex systems research.
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