Quasar Photometric Redshifts and Candidate Selection: A New Algorithm Based on Optical and Mid-infrared Photometric Data

Abstract

We present a new algorithm to estimate quasar photometric redshifts (photo-zs), by considering the asymmetries in the relative flux distributions of quasars. The relative flux models are built with multivariate Skew-t distributions in the multi-dimensional space of relative fluxes as a function of redshift and magnitude. For 151,392 quasars in the SDSS, we achieve a photo-z accuracy, defined as the fraction of quasars with the difference between the photo-z z p and the spectroscopic redshift z s , |∆z| = |z s − z p |/(1 + z s ) within 0.1, of 74%. Combining the WISE W1 and W2 infrared data with the SDSS data, the photo-z accuracy is enhanced to 87%. Using the Pan-STARRS1 or DECaLS photometry with WISE W1 and W2 data, the photo-z accuracies are 79% and 72%, respectively. The prior probabilities as a function of magnitude for quasars, stars and galaxies are calculated respectively based on (1) the quasar luminosity function; (2) the Milky Way synthetic simulation with the Besançon model; (3) the Bayesian Galaxy Photometric Redshift estimation. The relative fluxes of stars are obtained with the Padova isochrones, and the relative fluxes of galaxies are modeled through galaxy templates. We test our classification method to select quasars using the DECaLS g, r, z, and WISE W1 and W2 photometry. The quasar selection completeness is higher than 70% for a wide redshift range 0.5 < z < 4.5, and a wide magnitude range 18 < r < 21.5 mag. Our photo-z regression and classification method has the potential to extend to future surveys. The photo-z code will be publicly available.

Varstrometry for Off-nucleus and Dual sub-Kpc AGN (VODKA): Hubble Space Telescope Discovers Double Quasars

“…For the 57 observed targets without a spectroscopic redshift, we estimate photometric redshifts (photo-zs) with Skewt-QSO 1 . Skewt-QSO can achieve a photo-z accuracy, defined as the fraction of quasars with the difference between the photo-z and the spectroscopic redshift within 0.1, of 72%-79% using optical photometry from Pan-STARRS1 or DECaLS with WISE W1 and W2 data (Yang et al 2017). We use optical photometric data from Pan-STARRS1, or Gaia if Pan-STARRS1 is not available, in combination with WISE W1 and W2 mid-infrared photometry.…”

The Southern Photometric Local Universe Survey (S-PLUS): improved SEDs, morphologies, and redshifts with 12 optical filters

“…Several other authors have also used WISE bands to separate quasars from stars, in particular to increase the numbers of quasars at the bright end of the luminosity function (e.g. Schindler et al 2017;Yang et al 2017;Guo et al 2018). Earlier works based on the COMBO-17 survey had already discussed direct detection of emission lines in quasars through narrow-band optical SED (e.g.…”

Efficient selection of quasar candidates based on optical and infrared photometric data using machine learning

“…Since obtaining spectral redshifts is inefficient and expensive, using photometric information to obtain quasar redshifts has become a research interest (Richards et al 2001;Budavári et al 2001;Weinstein et al 2004;Ball et al 2007). Yang et al (2017) presented a new algorithm to estimate quasar photometric redshifts (photo-zs) by considering the asymmetries in the relative flux distributions of quasars. Schindler et al (2017) used SVM regression(SVR) and random forest (RF) regression to estimate quasar photometric redshifts with adjacent flux ratios.…”