Publication | Open Access
Transient Dissipation and Structural Costs of Physical Information Transduction
29
Citations
39
References
2017
Year
EngineeringInformation TheoryPhysicsEntropyUncertainty QuantificationComputational NeuroscienceEntropy ProductionComplexity TheoryAlgorithmic Information TheoryComputational ComplexityBiological SystemsComputer ScienceTransient DissipationStochastic ThermodynamicsKolmogorov ComplexityInformation Flow
A central result that arose in applying information theory to the stochastic thermodynamics of nonlinear dynamical systems is the information-processing second law (IPSL): the physical entropy of the Universe can decrease if compensated by the Shannon-Kolmogorov-Sinai entropy change of appropriate information-carrying degrees of freedom. In particular, the asymptotic-rate IPSL precisely delineates the thermodynamic functioning of autonomous Maxwellian demons and information engines. How do these systems begin to function as engines, Landauer erasers, and error correctors? We identify a minimal, and thus inescapable, transient dissipation of physical information processing, which is not captured by asymptotic rates, but is critical to adaptive thermodynamic processes such as those found in biological systems. A component of transient dissipation, we also identify an implementation-dependent cost that varies from one physical substrate to another for the same information processing task. Applying these results to producing structured patterns from a structureless information reservoir, we show that "retrodictive" generators achieve the minimal costs. The results establish the thermodynamic toll imposed by a physical system's structure as it comes to optimally transduce information.
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