Entropy balance and Information processing in bipartite and non-bipartite composite systems
Richard E. Spinney, Joseph T. Lizier, Mikhail Prokopenko

TL;DR
This paper develops a formal analogy between information dynamics and stochastic thermodynamics, introducing irreversibility measures for complex systems, including non-bipartite ones, and generalizing the second law of thermodynamics.
Contribution
It introduces a novel formalism linking information processing measures with thermodynamic irreversibility in both bipartite and non-bipartite systems.
Findings
Irreversibility measures are constructed from information theoretic quantities.
The formalism applies to non-bipartite processes, identifying heat flow and irreversibility.
Generalized second laws are derived for complex systems without bipartite structure.
Abstract
Information dynamics is an emerging description of information processing in complex systems which describes systems in terms of intrinsic computation, identifying computational primitives of information storage and transfer. In this paper we make a formal analogy between information dynamics and stochastic thermodynamics which describes the thermal behaviour of small irreversible systems. As stochastic dynamics is increasingly being utilized to quantify the thermodynamics associated with the processing of information we suggest such an analogy is instructive, highlighting that existing thermodynamic quantities can be described solely in terms of extant information theoretic measures related to information processing. In this contribution we construct irreversibility measures in terms of these quantities and relate them to the physical entropy productions that characterise the behaviour…
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