Photometric redshifts for the SDSS Data Release 12

被引:149
作者
Beck, Robert [1 ,2 ]
Dobos, Laszlo [1 ]
Budavari, Tamas [2 ,3 ,4 ]
Szalay, Alexander S. [2 ]
Csabai, Istvan [1 ]
机构
[1] Eotvos Lorand Univ, Dept Phys Complex Syst, H-1117 Budapest, Hungary
[2] Johns Hopkins Univ, Dept Phys & Astron, Baltimore, MD 21218 USA
[3] Johns Hopkins Univ, Dept Appl Math & Stat, Baltimore, MD 21218 USA
[4] Johns Hopkins Univ, Dept Comp Sci, Baltimore, MD 21218 USA
关键词
methods: data analysis; techniques: photometric; catalogues; galaxies: distances and redshifts; DIGITAL SKY SURVEY; SPECTROSCOPIC TARGET SELECTION; STELLAR POPULATION SYNTHESIS; SURVEY VIPERS; DATA REDUCTION; SURVEY DESIGN; 000; GALAXIES; DEEP FIELD; EVOLUTION; EMISSION;
D O I
10.1093/mnras/stw1009
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
We present the methodology and data behind the photometric redshift data base of the Sloan Digital Sky Survey (SDSS) Data Release 12. 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 catalogue was augmented with data from other, publicly available spectroscopic surveys to mitigate target selection effects. The training set is comprised of 1976 978 galaxies, and extends up to redshift z a parts per thousand 0.8, with a useful coverage of up to z a parts per thousand 0.6. We provide photometric redshifts and realistic error estimates for the 208 474 076 galaxies of the SDSS primary photometric catalogue. We achieve an average bias of overline{\Delta {{\mathrm{norm}}} = {5.84 \times 10<^>{-5}}a standard deviation of sigma(Delta z(norm)) = 0.0205, and a 3 sigma utlier rate of P-o = 4.11 per cent 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.
引用
收藏
页码:1371 / 1381
页数:11
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