Information Functionals and the Notion of (Un)Certainty: Random Matrix Theory - Inspired Case

P. Garbaczewski Institute of Physics, University of Opole, Oleska 48, 45-052 Opole, Poland

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Received: 25 05 2007;

Information functionals allow one 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.

DOI: 10.12693/APhysPolA.112.619 PACS numbers: 02.50.-r, 03.65.-w, 05.45.-a