| 书目名称 | Information Thermodynamics on Causal Networks and its Application to Biochemical Signal Transduction |
| 编辑 | Sosuke Ito |
| 视频video | |
| 概述 | 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 |
| 丛书名称 | Springer Theses |
| 图书封面 |  |
| 描述 | 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. .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. . |
| 出版日期 | Book 2016 |
| 关键词 | Bayesian network; Causal Networks; Information thermodynamics; Maxwell’s demon; Transfer entropy; informa |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-10-1664-6 |
| isbn_softcover | 978-981-10-9415-6 |
| isbn_ebook | 978-981-10-1664-6Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer Science+Business Media Singapore 2016 |
发表于 2025-3-21 16:14:24
