THE SLOAN DIGITAL SKY SURVEY CO-ADD: A GALAXY PHOTOMETRIC REDSHIFT CATALOG

We present and describe a catalog of galaxy photometric redshifts (photo-z's) for the Sloan Digital Sky Survey (SDSS) Coadd Data. 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 {approx} 13 million objects classified as galaxies in the coadd with r < 24.5. The photo-z and photo-z error estimators are trained and validated on a sample of {approx} 89, 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 (CNOC2), the Deep Extragalactic Evolutionary Probe Data Release 3(DEEP2 DR3), the SDSS-III's Baryon Oscillation Spectroscopic Survey (BOSS), the Visible imaging Multi-Object Spectrograph - Very Large Telescope Deep Survey (VVDS) 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} = 0.036. After presenting our results and quality tests, we provide a short guide for users accessing the public data.

[1]  Ofer Lahav,et al.  ANNz: Estimating Photometric Redshifts Using Artificial Neural Networks , 2004 .

[2]  D. Schlegel,et al.  Maps of Dust IR Emission for Use in Estimation of Reddening and CMBR Foregrounds , 1997, astro-ph/9710327.

[3]  B. Yanny,et al.  The Sloan Digital Sky Survey monitor telescope pipeline , 2006 .

[4]  Y. Wadadekar.  Estimating Photometric Redshifts Using Support Vector Machines , 2004, astro-ph/0412005.

[5]  M. Way,et al.  NEW APPROACHES TO PHOTOMETRIC REDSHIFT PREDICTION VIA GAUSSIAN PROCESS REGRESSION IN THE SLOAN DIGITAL SKY SURVEY , 2009, 0905.4081.

[6]  M. Fukugita,et al.  Statistical Properties of Bright Galaxies in the Sloan Digital Sky Survey Photometric System , 2001, astro-ph/0105401.

[7]  M. Shmakova,et al.  The Efficacy of Galaxy Shape Parameters in Photometric Redshift Estimation: A Neural Network Approach , 2011, 1101.4011.

[8]  THE DEEP GROTH STRIP GALAXY REDSHIFT SURVEY. III. REDSHIFT CATALOG AND PROPERTIES OF GALAXIES , 2004, astro-ph/0411128.

[9]  J. A. Smith,et al.  SDSS data management and photometric quality assessment , 2004 .

[10]  Walter A. Siegmund,et al.  The 2.5 m Telescope of the Sloan Digital Sky Survey , 2006, astro-ph/0602326.

[11]  et al,et al.  The Sloan Digital Sky Survey Photometric Camera , 1998, astro-ph/9809085.

[12]  Changbom Park,et al.  Morphology Segregation of Galaxies in Color-Color Gradient Space , 2005, astro-ph/0511385.

[13]  Alexander S. Szalay,et al.  Sloan digital sky survey: Early data release , 2002 .

[14]  R. J. Assef,et al.  Low Resolution Spectral Templates for AGNs and Galaxies , 2009, 0909.3849.

[15]  Karl Glazebrook,et al.  The WiggleZ Dark Energy Survey: survey design and first data release , 2009, 0911.4246.

[16]  K. Abazajian,et al.  THE SEVENTH DATA RELEASE OF THE SLOAN DIGITAL SKY SURVEY , 2008, 0812.0649.

[17]  D. Schlegel,et al.  Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds , 1998 .

[18]  D. Lambas,et al.  Photometric redshifts and K-corrections for Sloan Digital Sky Survey Seven Data Release , 2010, 1012.3752.

[19]  A. Fontana,et al.  Photometric redshifts with the Multilayer Perceptron Neural Network: Application to the HDF-S and SDSS , 2003, astro-ph/0312064.

[20]  E. al.,et al.  The Sloan Digital Sky Survey: Technical summary , 2000, astro-ph/0006396.

[21]  M. Fukugita,et al.  The Sloan Digital Sky Survey Photometric System , 1996 .

[22]  S. Okamura,et al.  Morphological Classification of Galaxies Using Photometric Parameters: The Concentration Index versus the Coarseness Parameter , 2005, astro-ph/0507060.

[23]  F. Miller Maley,et al.  An Efficient Algorithm for Positioning Tiles in the Sloan Digital Sky Survey , 2001 .

[24]  F. M. Maley,et al.  An Efficient Targeting Strategy for Multiobject Spectrograph Surveys: the Sloan Digital Sky Survey “Tiling” Algorithm , 2001, astro-ph/0105535.

[25]  V. Narayanan,et al.  Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Main Galaxy Sample , 2002, astro-ph/0206225.

[26]  V. Narayanan,et al.  Spectroscopic Target Selection for the Sloan Digital Sky Survey: The Luminous Red Galaxy Sample , 2001, astro-ph/0108153.

[27]  A. Szalay,et al.  Slicing Through Multicolor Space: Galaxy Redshifts from Broadband Photometry , 1995, astro-ph/9508100.

[28]  P. Hall,et al.  The CNOC2 Field Galaxy Redshift Survey. I. The Survey and the Catalog for the Patch CNOC 0223+00 , 2000, astro-ph/0004026.

[29]  Anthony H. Gonzalez,et al.  LOW-RESOLUTION SPECTRAL TEMPLATES FOR ACTIVE GALACTIC NUCLEI AND GALAXIES FROM 0.03 TO 30 μm , 2010 .

[30]  Robert H. Becker,et al.  A SURVEY OF z ∼ 6 QUASARS IN THE SLOAN DIGITAL SKY SURVEY DEEP STRIPE. I. A FLUX-LIMITED SAMPLE AT zAB < 21 , 2007, 0708.2578.

[31]  Jeffrey M. Kubo,et al.  THE SLOAN DIGITAL SKY SURVEY COADD: 275 deg2 OF DEEP SLOAN DIGITAL SKY SURVEY IMAGING ON STRIPE 82 , 2011, The Astrophysical Journal.

[32]  Huan Lin,et al.  A Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6 , 2007, 0708.0030.

[33]  J. Gunn,et al.  A Photometricity and Extinction Monitor at the Apache Point Observatory , 2001, astro-ph/0106511.

[34]  John E. Davis,et al.  Sloan Digital Sky Survey: Early Data Release , 2002 .

[35]  R. Nichol,et al.  The Application of Photometric Redshifts to the SDSS Early Data Release , 2002, astro-ph/0211080.

[36]  A. Mazure,et al.  The Vimos VLT deep survey Global properties of 20 000 galaxies in the IAB < 22.5 WIDE survey , 2008, 0804.4568.

[37]  J. Frieman,et al.  Photometric Redshift Error Estimators , 2007, 0711.0962.

[38]  R. Lupton,et al.  Astrometric Calibration of the Sloan Digital Sky Survey , 2002, astro-ph/0211375.