THE SLOAN DIGITAL SKY SURVEY CO-ADD: A GALAXY PHOTOMETRIC REDSHIFT CATALOG
- Center for Particle Astrophysics, Fermi National Accelerator Laboratory, Batavia, IL 60510 (United States)
- Berkeley Center for Cosmological Physics, LBL and Department of Physics, University of California, Berkeley, CA 94720 (United States)
- Department of Astronomy and Astrophysics, The University of Chicago, Chicago, IL 60637 (United States)
We present and describe a catalog of galaxy photometric redshifts (photo-z) for the Sloan Digital Sky Survey (SDSS) Co-add Data. We use the artificial neural network (ANN) technique to calculate the photo-z and the nearest neighbor error method to estimate photo-z errors for {approx}13 million objects classified as galaxies in the co-add with r < 24.5. The photo-z and photo-z error estimators are trained and validated on a sample of {approx}83,000 galaxies that have SDSS photometry and spectroscopic redshifts measured by the SDSS Data Release 7 (DR7), the Canadian Network for Observational Cosmology Field Galaxy Survey, the Deep Extragalactic Evolutionary Probe Data Release 3, the VIsible imaging Multi-Object Spectrograph-Very Large Telescope Deep Survey, and the WiggleZ Dark Energy Survey. For the 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}{sub 68} = 0.031. After presenting our results and quality tests, we provide a short guide for users accessing the public data.
- OSTI ID:
- 22016299
- Journal Information:
- Astrophysical Journal, Journal Name: Astrophysical Journal Journal Issue: 1 Vol. 747; ISSN ASJOAB; ISSN 0004-637X
- Country of Publication:
- United States
- Language:
- English
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