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As part of the Sloan Digital Sky Survey IV the extended Baryon Oscillation Spectroscopic Survey (eBOSS) will improve measurements of the cosmological distance scale by applying the Baryon Acoustic Oscillation (BAO) method to quasar samples.…

We describe the algorithm for selecting quasar candidates for optical spectroscopy in the Sloan Digital Sky Survey. Quasar candidates are selected via their non-stellar colors in "ugriz" broad-band photometry, and by matching unresolved…

We present an algorithm for selecting an uniform sample of gravitationally lensed quasar candidates from low-redshift (0.6<z<2.2) quasars brighter than i=19.1 that have been spectroscopically identified in the SDSS. Our algorithm uses…

We present a model for spectrophotometric calibration errors in observations of quasars from the third generation of the Sloan Digital Sky Survey (SDSS-III) Baryon Oscillation Spectroscopic Survey (BOSS) and describe the correction…

Instrumentation and Methods for Astrophysics · Physics 2016-11-15 Daniel Margala , David Kirkby , Kyle Dawson , Stephen Bailey , Michael Blanton , Donald P. Schneider

(abridged) We describe the automated spectral classification, redshift determination, and parameter measurement pipeline in use for the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III (SDSS-III) as of Data…

We present a catalog of 1,172,157 quasar candidates selected from the photometric imaging data of the Sloan Digital Sky Survey (SDSS). The objects are all point sources to a limiting magnitude of i=21.3 from 8417 sq. deg. of imaging from…

We present a catalog of 100,563 unresolved, UV-excess (UVX) quasar candidates to g=21 from 2099 deg^2 of the Sloan Digital Sky Survey (SDSS) Data Release One (DR1) imaging data. Existing spectra of 22,737 sources reveals that 22,191 (97.6%)…

The SDSS-III BOSS Quasar survey will attempt to observe z>2.15 quasars at a density of at least 15 per square degree to yield the first measurement of the Baryon Acoustic Oscillations in the Ly-alpha forest. To help reaching this goal, we…

We develop an automated technique to measure quasar redshifts in the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS). Our technique is an extension of an earlier Gaussian process method for detecting…

Astrophysics of Galaxies · Physics 2020-09-16 Leah Fauber , Ming-Feng Ho , Simeon Bird , Christian R. Shelton , Roman Garnett , Ishita Korde

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…

We describe the algorithm used to select the Luminous Red Galaxy (LRG) sample for the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey IV (SDSS-IV) using photometric data from both the SDSS and the…

We present the Data Release 9 Quasar (DR9Q) catalog from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. The catalog includes all BOSS objects that were targeted as quasar candidates during the…

Baryonic Acoustic Oscillations (BAO) and their effects on the matter power spectrum can be studied by using the Lyman-alpha absorption signature of the matter density field along quasar (QSO) lines of sight. A measurement sufficiently…

Cosmology and Nongalactic Astrophysics · Physics 2009-10-21 Ch. Yeche , P. Petitjean , J. Rich , E. Aubourg , N. Busca , J. -Ch. Hamilton , J. -M. Le Goff , I. Paris , S. Peirani , Ch. Pichon , E. Rollinde , M. Vargas-Magana

We identify 885,503 type 1 quasar candidates to i<22 using the combination of optical and mid-IR photometry. Optical photometry is taken from the Sloan Digital Sky Survey-III: Baryon Oscillation Spectroscopic Survey (SDSS-III/BOSS), while…

We conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys. We use a Bayesian quasar selection algorithm (Richards et al.…

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