Information Thermodynamics On Causal Networks And Its Application To Biochemical Signal Transduction (springer Theses)
by Sosuke Ito /
2016 / English / PDF
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In this book the author presents a general formalism of
nonequilibrium thermodynamics with complex information flows
induced by interactions among multiple fluctuating systems.
In this book the author presents a general formalism of
nonequilibrium thermodynamics with complex information flows
induced by interactions among multiple fluctuating systems.
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.
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.
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.