Information theory demonstration of the Richardson cascade

Turbulence theory is usually concerned with the statistical moments of the velocity or its fluctuations. One could also analyze the implicit probability distributions. This is the purview of information theory. Here we use information theory, specifically the conditional entropy, to analyze (quasi-)2D turbulence. We recast Richardson's "eddy hypothesis" that large eddies break up into small eddies in time in the language of information theory. In addition to confirming Richardson's idea, we find that self-similarity and turbulent length scales reappear naturally. Not surprisingly, we also find that the direction of information transfer is the same as the direction of the cascade itself. Consequently, intermittency may be considered a necessary companion to all turbulent flows.