Random-matrix spectra as a time series.
Spectra of ordered eigenvalues of finite random matrices are interpreted as a time series. Data-adaptive 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 one to distinguish the two cases.
Instituto Nacional de Geriatría, Periférico Sur No. 2767, 10200 México D.F., Mexico and Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de México, 04510 México D.F., Mexico.
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Fossion
Posgrado en Ciencias Físicas, Universidad Nacional Autónoma de México, 04510 México D.F., Mexico.
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Torres Vargas
Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, 04510 México D.F., Mexico.
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López Vieyra