Templex: A bridge between homologies and templates for chaotic attractors
Gisela D Charó1, Christophe Letellier2, Denisse Sciamarella3
1CONICET-Universidad de Buenos Aires, Centro de Investigaciones del Mar y la Atmósfera (CIMA), C1428EGA CABA, Argentina.
Chaos (Woodbury, N.Y.)
|September 1, 2022
Summary
This study introduces templex, a novel method combining cell complexes and directed graphs, to analyze chaotic attractors by incorporating flow dynamics. Templex enables sophisticated characterization and classification of these complex dynamical systems.
Area of Science:
- Dynamical Systems Theory
- Algebraic Topology
- Chaos Theory
Background:
- Homology theory uses cell complexes for algebraic descriptions of spaces.
- Branched Manifold Analysis through Homologies (BMH) characterizes state space attractors via cell complexes and homology groups.
- Existing BMH methods do not account for the flow's action on the cell complex.
Purpose of the Study:
- To extend BMH by incorporating flow dynamics into cell complex analysis.
- To develop a new framework, templex, for a more comprehensive study of chaotic attractors.
- To accurately classify and characterize chaotic attractors using the novel templex approach.
Main Methods:
- Endowing cell complexes with a directed graph to represent flow direction between highest-dimensional cells.
- Developing the templex framework by combining cell complexes and directed graphs.
- Investigating well-known chaotic attractors, including Rössler, Lorenz, and Burke-Shaw attractors.
Main Results:
- The templex framework successfully incorporates flow action into the topological analysis of attractors.
- Templex allows for sophisticated characterization and accurate classification of chaotic attractors.
- A link was established between templex descriptions and existing template-based analyses of chaotic systems.
Conclusions:
- Templex provides a powerful new tool for analyzing and classifying chaotic attractors.
- The integration of flow dynamics significantly enhances the descriptive power of cell complex methods.
- This approach offers a robust method for understanding complex dynamical systems.
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