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Title: Calibrating photometric redshifts of luminous red galaxies

Journal Article · · Monthly Notices of the Royal Astronomical Society
 [1];  [2];  [1];  [3];  [4];  [5];  [6];  [5];  [7];  [8];  [9];  [10];  [11];  [12];  [8];  [13];  [14];  [6];  [1];  [15] more »;  [16];  [2];  [17] « less
  1. Princeton Univ., Princeton, NJ (United States)
  2. Johns Hopkins Univ., Baltimore, MD (United States)
  3. Queen's Univ., Kingston, ON (Canada)
  4. Apache Point Observatory, Sunspot, MN (United States)
  5. Anglo-Australian Observatory, Epping, NSW (Australia)
  6. Univ. of Pittsburgh, Pittsburgh, PA (United States)
  7. Eotvos Univ., Budapest (Hungary)
  8. Univ. of Queensland (Australia)
  9. Steward Observatory, Tucson, AZ (United States)
  10. Institute of Astronomy, Cambridge (United Kingdom)
  11. Univ. of Sussex, Brighton (United Kingdom)
  12. Univ. of Portsmouth, Portsmouth (United Kingdom)
  13. Australian National Univ., Weston, ACT (Australia)
  14. Pennsylvania State Univ., University Park, PA (United States)
  15. Univ. of Durham, Durham (United Kingdom)
  16. Institute of Astronomy, Honolulu, HI (United States)
  17. Carnegie Mellon Univ., Pittsburgh, PA (United States)
+ Show Author Affiliations

We discuss the construction of a photometric redshift catalogue of luminous red galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS), emphasizing the principal steps necessary for constructing such a catalogue: (i) photometrically selecting the sample, (ii) measuring photometric redshifts and their error distributions, and (iii) estimating the true redshift distribution. We compare two photometric redshift algorithms for these data and find that they give comparable results. Calibrating against the SDSS and SDSS–2dF (Two Degree Field) spectroscopic surveys, we find that the photometric redshift accuracy is σ~ 0.03 for redshifts less than 0.55 and worsens at higher redshift (~ 0.06 for z < 0.7). These errors are caused by photometric scatter, as well as systematic errors in the templates, filter curves and photometric zero-points. We also parametrize the photometric redshift error distribution with a sum of Gaussians and use this model to deconvolve the errors from the measured photometric redshift distribution to estimate the true redshift distribution. We pay special attention to the stability of this deconvolution, regularizing the method with a prior on the smoothness of the true redshift distribution. The methods that we develop are applicable to general photometric redshift surveys.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1379844
Journal Information:
Monthly Notices of the Royal Astronomical Society, Vol. 359, Issue 1; ISSN 0035-8711
Publisher:
Royal Astronomical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 94 works
Citation information provided by
Web of Science

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Cited By (21)

Optical Cluster Finding with an Adaptive Matched‐Filter Technique: Algorithm and Comparison with Simulations journal April 2008
The clustering of luminous red galaxies in the Sloan Digital Sky Survey imaging data journal June 2007
Systematic errors in weak lensing: application to SDSS galaxy-galaxy weak lensing journal August 2005
Estimating the redshift distribution of photometric galaxy samples - II. Applications and tests of a new method journal July 2009
amico galaxy clusters in KiDS-DR3: sample properties and selection function journal January 2019
Dark Energy Survey year 1 results: galaxy sample for BAO measurement journal September 2018
Optimizing galaxy samples for clustering measurements in photometric surveys journal November 2019
Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data journal March 2019
Pan-STARRS1 variability of XMM-COSMOS AGN: I. Impact on photometric redshifts⋆⋆⋆ journal December 2015
Modelling the angular correlation function and its full covariance in photometric galaxy surveys: Angular clustering in photometric surveys journal March 2011
Data Mining and Machine Learning in Astronomy journal July 2010
Baryon Oscillations and Consistency Tests for Photometrically Determined Redshifts of Very Faint Galaxies journal June 2006
The imprints of primordial non-gaussianities on large-scale structure: scale dependent bias and abundance of virialized objects text January 2007
Estimating the Redshift Distribution of Photometric Galaxy Samples II. Applications and Tests of a New Method text January 2008
Data Mining and Machine Learning in Astronomy text January 2009
Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data text January 2018
AMICO galaxy clusters in KiDS-DR3: sample properties and selection function text January 2018
Optimizing galaxy samples for clustering measurements in photometric surveys text January 2019
Systematic errors in weak lensing: application to SDSS galaxy-galaxy weak lensing text January 2005
Baryon Oscillations and Consistency Tests for Photometrically-Determined Redshifts of Very Faint Galaxies text January 2005
The Clustering of Luminous Red Galaxies in the Sloan Digital Sky Survey Imaging Data text January 2006

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79 ASTRONOMY AND ASTROPHYSICS
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