Entropy (Feb 2019)

Information Thermodynamics for Time Series of Signal-Response Models

  • Andrea Auconi,
  • Andrea Giansanti,
  • Edda Klipp

DOI
https://doi.org/10.3390/e21020177
Journal volume & issue
Vol. 21, no. 2
p. 177

Abstract

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The entropy production in stochastic dynamical systems is linked to the structure of their causal representation in terms of Bayesian networks. Such a connection was formalized for bipartite (or multipartite) systems with an integral fluctuation theorem in [Phys. Rev. Lett. 111, 180603 (2013)]. Here we introduce the information thermodynamics for time series, that are non-bipartite in general, and we show that the link between irreversibility and information can only result from an incomplete causal representation. In particular, we consider a backward transfer entropy lower bound to the conditional time series irreversibility that is induced by the absence of feedback in signal-response models. We study such a relation in a linear signal-response model providing analytical solutions, and in a nonlinear biological model of receptor-ligand systems where the time series irreversibility measures the signaling efficiency.

Keywords