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Multiplex recurrence networks.

Deniz Eroglu1,2, Norbert Marwan1, Martina Stebich3

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Summary
This summary is machine-generated.

We developed a multiplex recurrence network method to analyze complex time series data. This approach detects changes in system dynamics, offering new insights into palaeobotany and environmental science.

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Area of Science:

  • Complex systems analysis
  • Network science
  • Palaeobotany

Background:

  • Multivariate time series analysis is challenging.
  • Understanding regime shifts in complex systems requires advanced methods.

Purpose of the Study:

  • To introduce a novel multiplex recurrence network approach for investigating multivariate time series.
  • To demonstrate its utility in detecting dynamical regime changes.

Main Methods:

  • Combining recurrence networks with multiplex network approaches.
  • Applying the method to coupled map lattices and palaeobotanical data (pollen records).
  • Analyzing topological changes in the networks to identify regime shifts.

Main Results:

  • Topological changes in multiplex recurrence networks effectively detect regime changes.
  • The approach provides a holistic view of vegetation dynamics, surpassing classical pollen record interpretation.
  • Similar behavior among vegetation types is observed when a single environmental factor dominates.

Conclusions:

  • Multiplex recurrence networks offer a powerful tool for analyzing complex multivariate time series.
  • This method enhances the understanding of dynamical systems and ecological changes.
  • Environmental factors significantly influence the collective dynamics of vegetation types.