Calibrating photometric redshifts of luminous red galaxies

Nikhil Padmanabhan, Tamás Budavári, David J. Schlegel, Terry Bridges, Jonathan Brinkmann, Russell Cannon, Andrew J. Connolly, Scott M. Croom, István Csabai, Michael Drinkwater, Daniel J. Eisenstein, Paul C. Hewett, Jon Loveday, Robert C. Nichol, Kevin A. Pimbblet, Roberto De Propris, Donald P. Schneider, Ryan Scranton, Uroš Seljak, Tom ShanksIstván Szapudi, Alexander S. Szalay, David Wake

Research output: Contribution to journalArticlepeer-review

92 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)237-250
Number of pages14
JournalMonthly Notices of the Royal Astronomical Society
Volume359
Issue number1
DOIs
StatePublished - May 1 2005

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

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