Photometric redshifts for the SDSS Data Release 12
Abstract
We present the methodology and data behind the photometric redshift database of the Sloan Digital Sky Survey Data Release 12 (SDSS DR12). We adopt a hybrid technique, empirically estimating the redshift via local regression on a spectroscopic training set, then fitting a spectrum template to obtain K-corrections and absolute magnitudes. The SDSS spectroscopic catalog was augmented with data from other, publicly available spectroscopic surveys to mitigate target selection effects. The training set is comprised of galaxies, and extends up to redshift , with a useful coverage of up to . We provide photometric redshifts and realistic error estimates for the galaxies of the SDSS primary photometric catalog. We achieve an average bias of , a standard deviation of , and a outlier rate of when cross-validating on our training set. The published redshift error estimates and photometric error classes enable the selection of galaxies with high quality photometric redshifts. We also provide a supplementary error map that allows additional, sophisticated filtering of the data.
Cite
@article{arxiv.1603.09708,
title = {Photometric redshifts for the SDSS Data Release 12},
author = {Róbert Beck and László Dobos and Tamás Budavári and Alexander S. Szalay and István Csabai},
journal= {arXiv preprint arXiv:1603.09708},
year = {2016}
}
Comments
12 pages, 7 figures. Original submitted to MNRAS on 2016 March 03, revision submitted on 2016 April 21