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Morse Predecomposition of an Invariant Set.
Michał Lipiński1,2, Konstantin Mischaikow3, Marian Mrozek4
1Intitute of Science and Technology Austria (ISTA), Am Campus 1, 3400 Klosterneuburg, Austria.
We introduce Morse predecomposition, a generalization of Morse decomposition for dynamical systems. This new framework captures recurrent dynamics, offering a finer analysis of complex systems beyond gradient behavior.
Area of Science:
- Dynamical Systems Theory
- Topology and Geometry in Dynamics
Background:
- Morse decomposition is a standard tool for analyzing the gradient dynamics of isolated invariant sets.
- Existing methods struggle to fully capture the recurrent dynamics within these sets, particularly chain recurrent sets.
- A need exists for a more comprehensive framework to understand the full dynamics of isolated invariant sets.
Purpose of the Study:
- To introduce and define the concept of Morse predecomposition for isolated invariant sets.
- To generalize Morse decomposition by incorporating recurrent dynamics beyond purely gradient behavior.
- To provide a framework capable of finer analysis for chain recurrent sets.
Main Methods:
- Developed a new framework, Morse predecomposition, by relaxing the poset structure of Morse decomposition.
- Introduced the concept of 'links' to represent connections between set elements, replacing strict ordering.
- Utilized both combinatorial and classical dynamical systems settings for the generalization.
Main Results:
- Morse predecomposition successfully extends analysis to include recurrent components of dynamical systems.
- Proved that standard Morse decomposition is a special case of Morse predecomposition.
- Demonstrated that Morse predecomposition can be condensed to recover a Morse decomposition.
Conclusions:
- Morse predecomposition offers a more refined and comprehensive analysis of isolated invariant sets in dynamical systems.
- This generalization enhances the study of recurrent orbits and complex dynamics.
- The framework provides a valuable tool for understanding systems not fully described by gradient dynamics alone.
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