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

• Authors: P. Garbaczewski
• Languages of publication: EN

Abstracts

EN

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.

Keywords

EN

02.50.-r; 03.65.-w; 05.45.-a

Discipline

• 05.45.-a: Nonlinear dynamics and chaos(see also section 45 Classical mechanics of discrete systems; for chaos in fluid dynamics, see 47.52.+j; for chaos in superconductivity, see 74.40.De)
• 03.65.-w: Quantum mechanics[see also 03.67.-a Quantum information; 05.30.-d Quantum statistical mechanics; 31.30.J- Relativistic and quantum electrodynamics (QED) effects in atoms, molecules, and ions in atomic physics]
• 02.50.-r: Probability theory, stochastic processes, and statistics(see also section 05 Statistical physics, thermodynamics, and nonlinear dynamical systems)

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2007
• Volume: 112
• Issue: 4
• Pages: 619-634

Dates

published

2007-10

received

2007-05-25

Contributors

author

P. Garbaczewski

• Institute of Physics, University of Opole, Oleska 48, 45-052 Opole, Poland

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Identifiers

DOI

10.12693/APhysPolA.112.619