Kolmogorov-Sinai entropy and dissipation in driven classical Hamiltonian systems

Matheus Capela, Mikel Sanz, Enrique Solano, and Lucas C. Céleri
Phys. Rev. E 98, 052109 – Published 9 November 2018

Abstract

A central concept in the connection between physics and information theory is entropy, which represents the amount of information extracted from the system by the observer performing measurements in an experiment. Indeed, Jaynes' principle of maximum entropy allows to establish the connection between entropy in statistical mechanics and information entropy. In this sense, the dissipated energy in a classical Hamiltonian process, known as the thermodynamic entropy production, is connected to the relative entropy between the forward and backward probability densities. Recently, it was revealed that energetic inefficiency and model inefficiency, defined as the difference in mutual information that the system state shares with the future and past environmental variables, are equivalent concepts in Markovian processes. As a consequence, the question about a possible connection between model unpredictability and energetic inefficiency in the framework of classical physics emerges. Here, we address this question by connecting the concepts of random behavior of a classical Hamiltonian system, the Kolmogorov-Sinai entropy, with its energetic inefficiency, the dissipated work. This approach allows us to provide meaningful interpretations of information concepts in terms of thermodynamic quantities.

  • Received 21 May 2018

DOI:https://doi.org/10.1103/PhysRevE.98.052109

©2018 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyStatistical Physics & ThermodynamicsGeneral Physics

Authors & Affiliations

Matheus Capela1, Mikel Sanz2, Enrique Solano2,3,4, and Lucas C. Céleri1,*

  • 1Institute of Physics, Federal University of Goiás, 74690-900 Goiânia, Brazil
  • 2Department of Physical Chemistry, University of the Basque Country UPV/EHU, Apartado 644, E-48080 Bilbao, Spain
  • 3IKERBASQUE, Basque Foundation for Science, Maria Diaz de Haro 3, E-48013 Bilbao, Spain
  • 4Department of Physics, Shanghai University, Shanghai 200444, China

  • *lucas@chibebe.org

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Issue

Vol. 98, Iss. 5 — November 2018

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