Information dynamics is an emerging description of information processing in complex systems. In this paper we make a formal analogy between information dynamics and stochastic thermodynamics. As stochastic dynamics increasingly concerns itself with the processing of information we suggest such an analogy is instructive in providing hitherto unexplored insights into the implicit information processing that occurs in physical systems. Information dynamics describes systems in terms of intrinsic computation, identifying computational primitives of information storage and transfer. We construct irreversibility measures in terms of these quantities are relate them to the physical entropy productions that govern the behaviour of single and composite systems in stochastic thermodynamics illustrating them with simple examples. Moreover, we can apply such a formalism to systems which do not have a bipartite structure. In particular we demonstrate that, given suitable non-bipartite processes, the heat flow in a subsystem can still be identified and one requires the present formalism to recover generalisations of the second law. This opens up the possibility of describing all physical systems in terms of computation allowing us to propose a framework for discussing the reversibility of systems traditionally out of scope of stochastic thermodynamics.
Thermodynamics and the dynamics of information in distributed computation
Richard E. Spinney, Joseph T. Lizier, Mikhail Prokopenko