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Early warning signal for interior crises in excitable systems.
Rajat Karnatak1, Holger Kantz2, Stephan Bialonski2
1Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, 12587 Berlin, Germany.
Predicting critical transitions in dynamical systems is enhanced by a new early warning signal: critical attractor growth. This method identifies impending global bifurcations, improving predictions for climate and neural models.
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Area of Science:
- Complex Systems Science
- Dynamical Systems Theory
- Computational Neuroscience
Background:
- Predicting critical transitions in dynamical systems is crucial across scientific fields.
- Existing early warning signals primarily address local bifurcations and non-bifurcation transitions.
- A gap exists in predicting global bifurcations, particularly interior crises in excitable systems.
Purpose of the Study:
- To introduce and validate a novel early warning signal for impending global bifurcations.
- To demonstrate the applicability of this signal in diverse complex systems.
- To extend the predictability of transitions in dynamical systems.
Main Methods:
- Investigated characteristic scaling behavior termed 'critical attractor growth'.
- Applied the early warning signal to a conceptual climate model.
- Tested the signal in a model of coupled neurons exhibiting extreme events.
Main Results:
- Observed critical attractor growth as a reliable indicator of impending interior crises.
- Demonstrated this phenomenon in both chaotic and strange-nonchaotic attractors.
- Validated the signal's effectiveness in climate and neural network models.
Conclusions:
- Critical attractor growth is a novel and effective early warning signal for interior crises.
- This finding expands the range of predictable transitions in dynamical systems.
- The signal holds promise for predicting extreme events in complex systems.

