Preliminary Target Selection for the DESI Quasar (QSO) Sample
Christophe Yèche, Nathalie Palanque-Delabrouille, Charles-Antoine Claveau, David D. Brooks, Edmond Chaussidon, Tamara M. Davis, Kyle S. Dawson, Arjun Dey, Yutong Duan, Sarah Eftekharzadeh, Daniel J. Eisenstein, Enrique Gaztañaga, Robert Kehoe, Martin Landriau, Dustin Lang, Michael E. Levi, Aaron M. Meisner, Adam D. Myers, Jeffrey A. Newman, Claire Poppett, Francisco Prada, Anand Raichoor, David J. Schlegel, Michael Schubnell, Ryan Staten, Gregory Tarlé, Rongpu Zhou
Abstract
The DESI survey will measure large-scale structure using quasars as direct tracers of dark matter in the redshift range $0.9<z<2.1$ and using quasar Ly-$α$ forests at $z>2.1$. We present two methods to select candidate quasars for DESI based on imaging in three optical ($g, r, z$) and two infrared ($W1, W2$) bands. The first method uses traditional color cuts and the second utilizes a machine-learning algorithm.
