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Information thermodynamics on causal networks.

Sosuke Ito¹, Takahiro Sagawa

¹Department of Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.

Physical Review Letters

|November 19, 2013

Summary

We developed new thermodynamic laws for complex information flows between systems. Entropy production is limited by information flow, with implications for biochemical adaptation models.

Area of Science:

Physics
Information Theory
Thermodynamics

Background:

Complex systems involve interactions between multiple fluctuating entities.
Understanding nonequilibrium thermodynamics is crucial for these systems.
Information flow plays a key role in system dynamics.

Purpose of the Study:

To generalize the second law of thermodynamics and fluctuation theorem for complex information flows.
To incorporate informational quantities into thermodynamic laws.
To analyze the impact of causal network topology on entropy production.

Main Methods:

Characterizing nonequilibrium dynamics using causal networks (Bayesian networks).
Developing novel generalizations of thermodynamic laws.

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Analyzing information flow and entropy production relationships.

Main Results:

Novel generalizations of the second law of thermodynamics and fluctuation theorem were obtained.
An informational quantity, dependent on causal network topology, was introduced.
Entropy production in a system is bounded by inter-system information flow.

Conclusions:

The study provides a new framework for nonequilibrium thermodynamics of complex information flows.
The findings offer insights into the interplay between information and thermodynamics.
Demonstrated applicability using a biochemical adaptation model.