A Chaos Synchronization Diagnostic Using Peak Complexity
Author Information
Author(s): Lin Zhe, Pattanayak Arjendu K., Amigó José María, Montani Fernando
Primary Institution: United World College Changshu China; Department of Physics and Astronomy, Carleton College
Hypothesis
Can the Difference Time Series Peak Complexity (DTSPC) algorithm effectively measure synchronization in chaotic systems?
Conclusion
The DTSPC algorithm successfully quantifies the complexity of chaos synchronization dynamics and captures transitional behaviors between different synchronization regimes.
Supporting Evidence
- The DTSPC algorithm uses entropy to measure synchronization in chaotic systems.
- Results show that the DTSPC captures diverse synchronization behaviors.
- The method can be applied without access to the differential equations of the systems.
Takeaway
This study introduces a new way to measure how chaotic systems can synchronize with each other, even when they start off behaving very differently.
Methodology
The study uses the DTSPC algorithm to analyze peak patterns in the difference time series of coupled Lorenz systems.
Limitations
The study does not conduct exhaustive convergence analysis for the results.
Digital Object Identifier (DOI)
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