Predicting bifurcations of almost-invariant patterns: a set-oriented approach
Moussa Ndour, Kathrin Padberg-Gehle

TL;DR
This paper develops a set-oriented approach to predict bifurcations of almost-invariant flow patterns in dynamical systems, providing a theoretical framework for understanding critical transitions like vortex splitting in geophysical flows.
Contribution
It introduces a novel set-oriented method using Markov chains to analyze bifurcations of almost-invariant sets in parameter-dependent flows, linking spectral properties to pattern break-up.
Findings
Eigenvector sign structure indicates bifurcation points
Spectral analysis predicts pattern splitting
Application to Duffing oscillator confirms method effectiveness
Abstract
The understanding and prediction of sudden changes in flow patterns is of paramount importance in the analysis of geophysical flows as these rare events relate to critical phenomena such as atmospheric blocking, the weakening of the Gulf stream, or the splitting of the polar vortex. In this work our aim is to develop first steps towards a theoretical understanding of vortex splitting phenomena. To this end, we study bifurcations of global flow patterns in parameter-dependent two-dimensional incompressible flows, with the flow patterns of interest corresponding to specific invariant sets. Under small random perturbations these sets become almost-invariant and can be computed and studied by means of a set-oriented approach, where the underlying dynamics is described in terms of a reversible finite-state Markov chain. Almost-invariant sets are obtained from the sign structure of leading…
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Taxonomy
TopicsEcosystem dynamics and resilience · Complex Systems and Time Series Analysis · Nonlinear Dynamics and Pattern Formation
