A Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6

dc.creatorOyaizu, Hiroaki
dc.creatorLima, Marcos
dc.creatorCunha, Carlos E.
dc.creatorLin, Huan
dc.creatorFrieman, Joshua
dc.creatorSheldon, Erin S.
dc.date2007-07-31
dc.date.accessioned2026-07-07T11:52:52Z
dc.date.available2026-07-07T11:52:52Z
dc.descriptionWe present and describe a catalog of galaxy photometric redshifts (photo-z's) for the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6). We use the Artificial Neural Network (ANN) technique to calculate photo-z's and the Nearest Neighbor Error (NNE) method to estimate photo-z errors for ~ 77 million objects classified as galaxies in DR6 with r < 22. The photo-z and photo-z error estimators are trained and validated on a sample of ~ 640,000 galaxies that have SDSS photometry and spectroscopic redshifts measured by SDSS, 2SLAQ, CFRS, CNOC2, TKRS, DEEP, and DEEP2. For the two best ANN methods we have tried, we find that 68% of the galaxies in the validation set have a photo-z error smaller than sigma_{68} =0.021 or $0.024. After presenting our results and quality tests, we provide a short guide for users accessing the public data.
dc.description16 pages, 12 figures
dc.identifierhttps://arxiv.org/abs/0708.0030
dc.identifierhttp://arxiv.org/abs/0708.0030
dc.identifierAstrophys.J.674:768-783,2008
dc.identifierdoi:10.1086/523666
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/204333
dc.subjectAstrophysics
dc.titleA Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6
dc.typetext

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