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

机译:紧密耦合限制的残余预测信息流动:简约模型的分析见解

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摘要

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.
机译:在耦合系统中,预测信息从导致导致变量流动。可以通过使用转移熵或用于高斯变量来量化转移预测信息的量,而是通过GRANGER因果关系来量化。它是自然的,期望并且已经反复观察到紧密耦合不允许在导致和导致变量之间重建因果关系。这里,我们表明,对于从主方程携带到Fokker-Planck水平的交互社会组的模型,即使在无限耦合强度的极限中,残差预测信息流也可以保留一对单向耦合的变量。我们将这种现象追溯到与耦合强度的同步力和噪声强度缩放的问题。简化的模型描述允许我们推导出完全阐明确定性和随机模型部件之间相互作用的分析表达式。

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