Average Spectral Density of Multiparametric Gaussian Ensembles of Complex Matrices

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Hauptverfasser: Ansari, Mohd. Gayas, Shukla, Pragya
Format: Preprint
Veröffentlicht: 2023
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author Ansari, Mohd. Gayas
Shukla, Pragya
author_facet Ansari, Mohd. Gayas
Shukla, Pragya
contents A statistical description of part of a many body system often requires a non-Hermitian random matrix ensemble with nature and strength of randomness sensitive to underlying system conditions. For the ensemble to be a good description of the system, the ensemble parameters must be determined from the system parameters. This in turn makes its necessary to analyze a wide range of multi-parametric ensembles with different kinds of matrix elements distributions. The spectral statistics of such ensembles is not only system-dependent but also non-ergodic as well as non-stationary. A change in system conditions can cause a change in the ensemble parameters resulting an evolution of the ensemble density and it is not sufficient to know the statistics for a given set of system conditions. This motivates us to theoretically analyze a multiparametric evolution of the ensemble averaged spectral density of a multiparametric Gaussian ensemble on the complex plane. Our analysis reveals the existence of an evolutionary route common to the ensembles belonging to same global constraint class and thereby derives a complexity parameter dependent formulation of the spectral density for the non-equilibrium regime of the spectral statistics, away from Ginibre equilibrium limit.
format Preprint
id arxiv_https___arxiv_org_abs_2301_08850
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Average Spectral Density of Multiparametric Gaussian Ensembles of Complex Matrices
Ansari, Mohd. Gayas
Shukla, Pragya
Disordered Systems and Neural Networks
Statistical Mechanics
Mathematical Physics
A statistical description of part of a many body system often requires a non-Hermitian random matrix ensemble with nature and strength of randomness sensitive to underlying system conditions. For the ensemble to be a good description of the system, the ensemble parameters must be determined from the system parameters. This in turn makes its necessary to analyze a wide range of multi-parametric ensembles with different kinds of matrix elements distributions. The spectral statistics of such ensembles is not only system-dependent but also non-ergodic as well as non-stationary. A change in system conditions can cause a change in the ensemble parameters resulting an evolution of the ensemble density and it is not sufficient to know the statistics for a given set of system conditions. This motivates us to theoretically analyze a multiparametric evolution of the ensemble averaged spectral density of a multiparametric Gaussian ensemble on the complex plane. Our analysis reveals the existence of an evolutionary route common to the ensembles belonging to same global constraint class and thereby derives a complexity parameter dependent formulation of the spectral density for the non-equilibrium regime of the spectral statistics, away from Ginibre equilibrium limit.
title Average Spectral Density of Multiparametric Gaussian Ensembles of Complex Matrices
topic Disordered Systems and Neural Networks
Statistical Mechanics
Mathematical Physics
url https://arxiv.org/abs/2301.08850