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Multifractal structure of a riddled basin.
Hiromichi Suetani1, Takehiko Horita
1Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, JapanThe Institute of Statistical Mathematics, Tokyo 106-8569, Japan.
Chaos (Woodbury, N.Y.)
|June 5, 2003
Summary
Researchers introduced a multifractal spectrum to analyze riddled basins in dynamical systems. This spectrum helps define a boundary for these complex basins and relates to stable sets on chaotic attractors.
Area of Science:
- Dynamical Systems and Chaos Theory
- Fractal Geometry
- Nonlinear Dynamics
Background:
- Riddled basins are complex structures in two-dimensional piecewise linear maps.
- Characterizing the boundaries of these basins is crucial for understanding their dynamics.
- Existing methods struggle to fully describe the intricate nature of riddled basins.
Purpose of the Study:
- To introduce a multifractal spectrum, f(gamma), for characterizing the skeletons of riddled basins.
- To derive the uncertainty exponent using a variational principle based on f(gamma).
- To propose a concept of a boundary for riddled basins and explore its relation to stable sets.
Main Methods:
- Development of a multifractal spectrum, f(gamma), tailored for riddled basins.
- Application of a variational principle to obtain the uncertainty exponent from f(gamma).
- Analysis of the relationship between f(gamma) and stable sets of ergodic measures.
Main Results:
- The multifractal spectrum f(gamma) effectively characterizes the skeletons of riddled basins.
- A variational principle yields the uncertainty exponent, enabling a boundary definition.
- A conjecture is proposed linking f(gamma) to stable sets of coexisting ergodic measures.
Conclusions:
- The multifractal spectrum provides a novel tool for analyzing complex dynamical systems.
- The concept of a boundary for riddled basins is established through the uncertainty exponent.
- Further research is suggested on the interplay between multifractality and ergodic measures in chaotic attractors.