数理科学セミナー: Information thermodynamics on causal networks and its application to biochemical signal transduction (part II)

開催日時
2017年   5月 16日 17時 00分 ~ 2017年   5月 16日 18時 30分
場所
理3-307号室
講演者
伊藤創祐氏(北大電子研)
 
概要:
Unified theory of information and thermodynamics has been intensively discussed for nonequilibrium stochastic dynamics from the viewpoint of a thought experiment known as Maxwell's demon [1].
In this field, we have obtained the generalized second law of thermodynamics with information transfer, that is applicable to a broad class of dynamics such as autonomous biochemical reaction [2]. To prove the generalized second law of thermodynamics with information transfer, we have used a probabilistic graphical model known as Bayesian network for a mathematical description of complex nonequilibrium stochastic dynamics. Furthermore, we have also applied the generalized second law of thermodynamics with information transfer to biochemical signal transduction, e.g., sensory adaptation in E. coli bacterial chemotaxis [3]. From the view point of thermodynamics of information, we can quantitatively discuss a fundamental bound of information transfer in a biochemical sensor.
(If we have some time, I also would like to introduce recent progresses in thermodynamics of information, e.g., Onsager reciprocal relations for information transfer [4].)

[1] J. M. R. Parrondo, J. M. Horowitz, and T. Sagawa, Nature Physics 11, 131-139 (2015).
[2] S. Ito and T. Sagawa, Phys. Rev. Lett. 111, 180603 (2013).
[3] S. Ito and T. Sagawa, Nature Communications 6, 7498 (2015).
[4] S. Yamamoto, S. Ito, N. Shiraishi and T. Sagawa, Phys. Rev. E 94, 052121 (2016).

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