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Thermodynamic phase transitions for Pomeau-Manneville maps
1Centro de Matemática, Computação e Cognição, UFABC, 09210-170 Santo André, SP, Brazil. roberto.venegeroles@ufabc.edu.br
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 26, 2012
Summary
We explore phase transitions in Pomeau-Manneville intermittent maps using infinite ergodic theory. A distributional limit theorem helps calculate thermodynamic potentials and understand dynamic characteristics during instability phases.
Area of Science:
- Dynamical Systems and Chaos Theory
- Statistical Mechanics
- Information Theory
Background:
- Pomeau-Manneville maps exhibit intermittent behavior, a key characteristic of chaotic systems.
- Infinite ergodic theory provides tools to analyze systems with diverging measures, often found in complex dynamics.
- Understanding phase transitions is crucial for characterizing the behavior of dynamical systems.
Purpose of the Study:
- To investigate phase transitions in Pomeau-Manneville intermittent maps.
- To apply infinite ergodic theory and distributional limit theorems to these systems.
- To calculate thermodynamic potentials, topological pressure, and Rényi entropy.
Main Methods:
- Utilizing the framework of infinite ergodic theory.
- Applying a distributional limit theorem for analysis.
- Exact calculation of topological pressure and Rényi entropy.
Main Results:
- The distributional limit theorem serves as a powerful tool for calculating thermodynamic potentials.
- The theorem provides insights into dynamic characteristics across different instability phases.
- Exact values for topological pressure and Rényi entropy were determined.
- A connection was established between the distributional limit theorem and non-Gaussian fluctuations in algorithmic complexity.
Conclusions:
- Infinite ergodic theory offers a robust approach to studying phase transitions in intermittent maps.
- The distributional limit theorem is effective for both quantitative calculations and qualitative understanding of system dynamics.
- The findings link thermodynamic properties with information-theoretic concepts like algorithmic complexity.
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