Information thermodynamics of near-equilibrium computation

Mikhail Prokopenko, Itai Einav

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


In studying fundamental physical limits and properties of computational processes, one is faced with the challenges of interpreting primitive information-processing functions through well-defined information-theoretic as well as thermodynamic quantities. In particular, transfer entropy, characterizing the function of computational transmission and its predictability, is known to peak near critical regimes. We focus on a thermodynamic interpretation of transfer entropy aiming to explain the underlying critical behavior by associating information flows intrinsic to computational transmission with particular physical fluxes. Specifically, in isothermal systems near thermodynamic equilibrium, the gradient of the average transfer entropy is shown to be dynamically related to Fisher information and the curvature of system's entropy. This relationship explicitly connects the predictability, sensitivity, and uncertainty of computational processes intrinsic to complex systems and allows us to consider thermodynamic interpretations of several important extreme cases and trade-offs.

Original languageEnglish
Article number062143
Pages (from-to)062143-1-062143-8
Number of pages8
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Issue number6
Publication statusPublished - 29 Jun 2015
Externally publishedYes

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