Quasar Target Selection with WISE


Photo of Christophe Yeche
Christophe Yèche
IFRU, CEA Saclay, France


Spectra measured with the goal of enhancing the efficiency of quasar identification in SDSS

Finding Targets

An object whose ANCILLARY_TARGET2 value includes one or more of the bitmasks in the following table was targeted for spectroscopy as part of this ancillary target program. See SDSS bitmasks to learn how to use these values to identify objects in this ancillary target program.

Program (bit name) Bit number Target Description Number of Fibers Number of Unique Primary Objects
QSO_WISE_FULL_SKY 10 Quasar selected from the WISE All-Sky Survey 29,075 26,932


This ancillary target program was a second sample of WISE-selected quasars, focused on the redshift range z > 2.15.

The quasar target selection algorithms described in Ross et al. (2012) varied in efficiency in identifying z > 2.15 quasars for Lyman-alpha forest studies. For example, regions covered by the UKIRT Infrared Deep Sky Survey (UKIDSS; Lawrence et al. 2007) produced a higher density of high-redshift quasars than regions without UKIDSS data. As a means to enhance the efficiency of quasar identification in the area of sky observed in the final two years of SDSS-III, mid-infrared photometry from the WISE All-Sky survey.

Target Selection

Candidate quasars were identified from SDSS photometry using an artificial neural network as described in Yèche et al. (2010). Point sources are assigned a likelihood ranging from zero (stellar) to one (quasar) and a photometric redshift estimate. Objects with NN > 0:3 were considered targets if they were matched within 1.5″ of a WISE source, had color iPSF – W1 > 2.0 + 0.8(gPSF – iPSF – W2 > 3.0, and were brighter than gPSF = 21.5.

These color cuts were designed to identify high-redshift quasars, and indeed almost 3/4 of the candidates have redshifts above 2. Objects satisfying this cut were assigned the QSO_WISE_FULL_SKY flag whether or not they were also targeted by the main BOSS quasar target selection.


Lawrence, A., et al. 2007, MNRAS, 379, 1599
Ross, N. P., et al. 2012, ApJS, 199, 3
Wright, E. L., et al. 2010, AJ, 140, 1868
Yèeche, C., et al. 2010, A&A, 523, A14