Random Matrix Spectra as a Time Series

Abstract

Spectra of ordered eigenvalues of finite Random Matrices are interpreted as a time series. Dataadaptive techniques from signal analysis are applied to decompose the spectrum in clearly differentiated trend and fluctuation modes, avoiding possible artifacts introduced by standard unfolding techniques. The fluctuation modes are scale invariant and follow different power laws for Poisson and Gaussian ensembles, which already during the unfolding allows to distinguish the two cases.

Phys. Rev. E (Rapid Communication) [http://pre.aps.org/accepted/ca072R0eWe4Ebf1410bf6d37595695d4a4c8cd76f] Accepted for publication, Wednesday Nov 20, 2013

References in corpus (3)

• Quantum spectrum as a time series : Fluctuation measures
• Spectral analysis of deformed random networks
• Spectral fluctuations of tridiagonal random matrices from the beta-Hermite ensemble

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