Residual Predictive Information Flow in the Tight Coupling Limit: Analytic Insights from a Minimalistic Model

In a coupled system, predictive information flows from the causing to the caused variable. The amount of transferred predictive information can be quantified through the use of transfer entropy or, for Gaussian variables, equivalently via Granger causality. It is natural to expect and has been repea...

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Bibliographic Details
Published in:Entropy (Basel, Switzerland) Switzerland), 2019-10, Vol.21 (10), p.1010
Main Authors: Wahl, Benjamin, Feudel, Ulrike, Hlinka, Jaroslav, Wächter, Matthias, Peinke, Joachim, Freund, Jan A.
Format: Article
Language:English
Subjects:
Causality
Coupling
Information flow
information transfer
Noise
Stochastic models
Synchronism
Time series
Variables
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Summary:In a coupled system, predictive information flows from the causing to the caused variable. The amount of transferred predictive information can be quantified through the use of transfer entropy or, for Gaussian variables, equivalently via Granger causality. It is natural to expect and has been repeatedly observed that a tight coupling does not permit to reconstruct a causal connection between causing and caused variables. Here, we show that for a model of interacting social groups, carried from the master equation to the Fokker–Planck level, a residual predictive information flow can remain for a pair of uni-directionally coupled variables even in the limit of infinite coupling strength. We trace this phenomenon back to the question of how the synchronizing force and the noise strength scale with the coupling strength. A simplified model description allows us to derive analytic expressions that fully elucidate the interplay between deterministic and stochastic model parts.
ISSN:1099-4300
1099-4300
DOI:10.3390/e21101010