Overview
- Nominated as an outstanding contribution by the University of Tokyo's Physics Department in 2015
- Presents studies of a novel generalization of the second law of thermodynamics for small subsystems on causal networks
- Focusses on stochastic thermodynamics with information applicable to a broad class of nonequilibrium dynamics such as biochemical signal transduction
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Theses (Springer Theses)
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Table of contents (10 chapters)
Keywords
About this book
The author has generalized stochastic thermodynamics with information by using a graphical theory. Characterizing nonequilibrium dynamics by causal networks, he has obtained a novel generalization of the second law of thermodynamics with information that is applicable to quite a broad class of stochastic dynamics such as information transfer between multiple Brownian particles, an autonomous biochemical reaction, and complex dynamics with a time-delayed feedback control. This study can produce further progress in the study of Maxwell’s demon for special cases.
As an application to these results, information transmission and thermodynamic dissipation in biochemical signal transduction are discussed. The findings presented here can open up a novel biophysical approach to understanding information processing in living systems.
Authors and Affiliations
About the author
Dr. Sosuke Ito
Department of Physics, The University of Tokyo
Bibliographic Information
Book Title: Information Thermodynamics on Causal Networks and its Application to Biochemical Signal Transduction
Authors: Sosuke Ito
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-981-10-1664-6
Publisher: Springer Singapore
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer Science+Business Media Singapore 2016
Hardcover ISBN: 978-981-10-1662-2Published: 26 July 2016
Softcover ISBN: 978-981-10-9415-6Published: 31 May 2018
eBook ISBN: 978-981-10-1664-6Published: 16 July 2016
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XIII, 133
Number of Illustrations: 4 b/w illustrations, 28 illustrations in colour
Topics: Thermodynamics, Complex Systems, Quantum Information Technology, Spintronics, Biological and Medical Physics, Biophysics, Numerical and Computational Physics, Simulation, Statistical Physics and Dynamical Systems