Information functionals and the notion of (un)certainty: RMT - inspired case

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Information functionals allow to quantify the degree of randomness of a given probability distribution, either absolutely (through min/max entropy principles) or relative to a prescribed reference one. Our primary aim is to analyze the "minimum information" assumption, which is a classic concept (R. Balian, 1968) in the random matrix theory. We put special emphasis on generic level (eigenvalue) spacing distributions and the degree of their randomness, or alternatively - information/organization deficit.
Presented at the 3rd Workshop on Quantum Chaos and Localization Phenomena, Warsaw May 25-27,2007

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