Nonparametric goodness-of fit testing in quantum homodyne tomography with noisy data

dc.creatorMeziani, Katia
dc.date2008-08-23
dc.date2008-12-22
dc.date.accessioned2026-07-07T12:20:46Z
dc.date.available2026-07-07T12:20:46Z
dc.descriptionIn the framework of quantum optics, we study the problem of goodness-of-fit testing in a severely ill-posed inverse problem. A novel testing procedure is introduced and its rates of convergence are investigated under various smoothness assumptions. The procedure is derived from a projection-type estimator, where the projection is done in $\mathbb{L}_2$ distance on some suitably chosen pattern functions. The proposed methodology is illustrated with simulated data sets.
dc.descriptionPublished in at http://dx.doi.org/10.1214/08-EJS286 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0808.3194
dc.identifierhttp://arxiv.org/abs/0808.3194
dc.identifierElectronic Journal of Statistics 2008, Vol. 2, 1195-1223
dc.identifierdoi:10.1214/08-EJS286
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/213160
dc.subjectStatistics Theory
dc.subject62G05, 62G10, 62G20 (Primary) 81V80 (Secondary)
dc.titleNonparametric goodness-of fit testing in quantum homodyne tomography with noisy data
dc.typetext

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