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dc.rights.licensehttp://creativecommons.org/licenses/by/4.0es_MX
dc.creatorRUBEN YVAN MAARTEN FOSSIONes_MX
dc.creatorGAMALIEL TORRES VARGASes_MX
dc.creatorJUAN CARLOS LOPEZ VIEYRAes_MX
dc.date2013
dc.date.accessioned2021-10-28T18:49:28Z
dc.date.available2021-10-28T18:49:28Z
dc.identifier.urihttp://repositorio.inger.gob.mx/jspui/handle/20.500.12100/17291
dc.descriptionSpectra 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.es_MX
dc.formatAdobe PDFes_MX
dc.languageenges_MX
dc.publisherAmerican Physical Societyes_MX
dc.relationhttps://journals.aps.org/pre/abstract/10.1103/PhysRevE.88.060902es_MX
dc.relation.requiresSies_MX
dc.rightsAcceso Abiertoes_MX
dc.sourcePhysical Review E (2470-0053) Vol. 88 (2013)es_MX
dc.subjectCIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRAes_MX
dc.subjectFísicaes_MX
dc.subjectFísica moleculares_MX
dc.subjectEspectroscopía moleculares_MX
dc.subjectCiencias no linealeses_MX
dc.subjectDinámica caóticaes_MX
dc.subjectPhysicses_MX
dc.subjectMolecular physicses_MX
dc.subjectMolecular spectroscopyes_MX
dc.subjectNonlinear scienceses_MX
dc.subjectChaotic dinamicses_MX
dc.titleRandom-matrix spectra as a time serieses_MX
dc.typeArtículoes_MX
dc.audienceResearcherses_MX
dc.creator.idFOXR771115HNESXB09es_MX
dc.creator.idTOVG860926HHGRRM01es_MX
dc.creator.idLOVJ610612HDFPYN03es_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX


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