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Polyadic Entropy, Synergy and Redundancy among Statistically Independent Processes in Nonlinear Statistical Physics
1Institute of Hydraulic Engineering, Technische Universität Wien (TU Wien), Karlsplatz 13/222, 1040 Vienna, Austria.
Entropy (Basel, Switzerland)
|December 3, 2020
Summary
Generalized entropy measures reveal how microscale interactions influence macroscale information. This study quantifies emergent information from nonlinear microphysics, highlighting synergy and redundancy in coevolutionary systems.
Area of Science:
- Information Theory
- Statistical Physics
- Complex Systems
Background:
- Traditional information measures assume memoryless processes and lack microstate interactions.
- Non-extensive statistical mechanics offers generalized entropy to account for microphysical codependence.
Purpose of the Study:
- To investigate and quantify the emergence of macroscale information from microscale codependence.
- To evaluate how microphysical interactions impact information measures across scales.
Main Methods:
- Utilizing generalized entropy measures from non-extensive statistical mechanics.
- Evaluating redundancy and synergy among statistically independent macroscale variables.
- Analyzing information emergence solely from nonlinear microphysics.
Main Results:
- Synergistic and redundant information emerge from microphysical interactions, even with factorable distributions.
- Macroscale information is shown to emerge from microscale codependence.
- Nonlinear statistical physics provides added value to information theory in coevolutionary systems.
Conclusions:
- Microscale codependence significantly influences macroscale information.
- Nonlinear interactions are crucial for understanding information flow in complex systems.
- This work bridges information theory and nonlinear statistical physics for coevolutionary dynamics.
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