Random-matrix spectra as a time series

摘要

Spectra of ordered eigenvalues of finite random matrices are interpreted as a time series. Data-adaptiventechniques from signal analysis are applied to decompose the spectrum in clearly differentiated trend andnfluctuation modes, avoiding possible artifacts introduced by standard unfolding techniques. The fluctuationnmodes are scale invariant and follow different power laws for Poisson and Gaussian ensembles, which alreadynduring the unfolding allows one to distinguish the two cases.