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Titolo:
REAL SYMMETRICAL RANDOM-MATRIX ENSEMBLES OF HAMILTONIANS WITH PARTIALSYMMETRY-BREAKING
Autore:
LEITNER DM;
Indirizzi:
UNIV HEIDELBERG,IM NEUENHEIMER FELD 253 W-6900 HEIDELBERG GERMANY
Titolo Testata:
Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
fascicolo: 4, volume: 48, anno: 1993,
pagine: 2536 - 2546
SICI:
1063-651X(1993)48:4<2536:RSREOH>2.0.ZU;2-#
Fonte:
ISI
Lingua:
ENG
Soggetto:
STATISTICAL PROPERTIES; LEVEL SPACINGS; SPECTRA; FLUCTUATIONS; INTEGRABILITY; TRANSITION; TRANSPORT; BEHAVIOR; MOTION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
34
Recensione:
Indirizzi per estratti:
Citazione:
D.M. Leitner, "REAL SYMMETRICAL RANDOM-MATRIX ENSEMBLES OF HAMILTONIANS WITH PARTIALSYMMETRY-BREAKING", Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 48(4), 1993, pp. 2536-2546

Abstract

We investigate random matrix ensembles E(epsilon) containing real symmetric matrices H=H(0)+epsilonV, where H(0) is block diagonal, each block a member of the Gaussian orthogonal ensemble, coupled together by the Gaussian random elements of epsilon(V). E(epsilon) could model, for example, a chaotic Hamiltonian apart from an approximate integral ofthe motion. We focus on transitions in eigenvalue and eigenvector projection statistics of E(epsilon) upon variation of their respective scaling parameters. Expressions for the probability density of nearest-neighbor level spacings as well as the spectral rigidity are given, andsupported by numerical data, and their application in determining a symmetry-breaking perturbation is discussed. We derive an expression for the probability density of projections of eigenvectors of E(epsilon)onto those of E(0) valid for sufficiently small epsilon and use it tocalculate ensemble averages and distribution functions. Each of theseresults is compared with numerical data. We furthermore use E(epsilon) at small epsilon to calculate average time-dependent transition probabilities of nonstationary states.

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Documento generato il 28/09/20 alle ore 17:19:04