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Think outside the color box: Probabilistic target selection and the SDSS-XDQSO quasar targeting catalog

  • Jo Bovy
  • , Joseph F. Hennawi
  • , David W. Hogg
  • , Adam D. Myers
  • , Jessica A. Kirkpatrick
  • , David J. Schlegel
  • , Nicholas P. Ross
  • , Erin S. Sheldon
  • , Ian D. McGreer
  • , Donald P. Schneider
  • , Benjamin A. Weaver

Research output: Contribution to journalArticlepeer-review

Abstract

We present the SDSS-XDQSO quasar targeting catalog for efficient flux-based quasar target selection down to the faint limit of the Sloan Digital Sky Survey (SDSS) catalog, even at medium redshifts (2.5 ≲ z ≲ 3) where the stellar contamination is significant. We build models of the distributions of stars and quasars in flux space down to the flux limit by applying the extreme-deconvolution method to estimate the underlying density. We convolve this density with the flux uncertainties when evaluating the probability that an object is a quasar. This approach results in a targeting algorithm that is more principled, more efficient, and faster than other similar methods. We apply the algorithm to derive low-redshift (z < 2.2), medium-redshift (2.2 ≤ z ≤ 3.5), and high-redshift (z>3.5) quasar probabilities for all 160,904,060 point sources with dereddened i-band magnitude between 17.75 and 22.45mag in the 14,555deg2 of imaging from SDSS Data Release 8. The catalog can be used to define a uniformly selected and efficient low- or medium-redshift quasar survey, such as that needed for the SDSS-III's Baryon Oscillation Spectroscopic Survey project. We show that the XDQSO technique performs as well as the current best photometric quasar-selection technique at low redshift, and outperforms all other flux-based methods for selecting the medium-redshift quasars of our primary interest. We make code to reproduce the XDQSO quasar target selection publicly available.

Original languageEnglish (US)
Article number141
JournalAstrophysical Journal
Volume729
Issue number2
DOIs
StatePublished - Mar 10 2011

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

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