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Title: PHOTOMETRIC REDSHIFT PROBABILITY DISTRIBUTIONS FOR GALAXIES IN THE SDSS DR8

Journal Article · · Astrophysical Journal, Supplement Series
 [1];  [2];  [3];  [4];  [5]
  1. Brookhaven National Laboratory, Bldg 510, Upton, NY 11973 (United States)
  2. Department of Physics, University of Michigan, 500 East University, Ann Arbor, MI 48109-1120 (United States)
  3. Princeton University Observatory, Peyton Hall, Princeton, NJ 08544 (United States)
  4. Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349 (United States)
  5. Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States)

We present redshift probability distributions for galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 8 imaging data. We used the nearest-neighbor weighting algorithm to derive the ensemble redshift distribution N(z), and individual redshift probability distributions P(z) for galaxies with r < 21.8 and u < 29.0. As part of this technique, we calculated weights for a set of training galaxies with known redshifts such that their density distribution in five-dimensional color-magnitude space was proportional to that of the photometry-only sample, producing a nearly fair sample in that space. We estimated the ensemble N(z) of the photometric sample by constructing a weighted histogram of the training-set redshifts. We derived P(z)'s for individual objects by using training-set objects from the local color-magnitude space around each photometric object. Using the P(z) for each galaxy can reduce the statistical error in measurements that depend on the redshifts of individual galaxies. The spectroscopic training sample is substantially larger than that used for the DR7 release. The newly added PRIMUS catalog is now the most important training set used in this analysis by a wide margin. We expect the primary sources of error in the N(z) reconstruction to be sample variance and spectroscopic failures: The training sets are drawn from relatively small volumes of space, and some samples have large incompleteness. Using simulations we estimated the uncertainty in N(z) due to sample variance at a given redshift to be {approx}10%-15%. The uncertainty on calculations incorporating N(z) or P(z) depends on how they are used; we discuss the case of weak lensing measurements. The P(z) catalog is publicly available from the SDSS Web site.

OSTI ID:
22047591
Journal Information:
Astrophysical Journal, Supplement Series, Vol. 201, Issue 2; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 0067-0049
Country of Publication:
United States
Language:
English

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