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Preliminary Target Selection for the DESI Quasar (QSO) Sample

Authors :
Yèche, Christophe
Palanque-Delabrouille, Nathalie
Claveau, Charles-Antoine
Brooks, David D.
Chaussidon, Edmond
Davis, Tamara M.
Dawson, Kyle S.
Dey, Arjun
Duan, Yutong
Eftekharzadeh, Sarah
Eisenstein, Daniel J.
Gaztañaga, Enrique
Kehoe, Robert
Landriau, Martin
Lang, Dustin
Levi, Michael E.
Meisner, Aaron M.
Myers, Adam D.
Newman, Jeffrey A.
Poppett, Claire
Prada, Francisco
Raichoor, Anand
Schlegel, David J.
Schubnell, Michael
Staten, Ryan
Tarlé, Gregory
Zhou, Rongpu
Source :
Research Notes of the AAS, 2020, 4, 10, 179
Publication Year :
2020

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-$\alpha$ 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.<br />Comment: 3 pages, 1 figure

Details

Database :
arXiv
Journal :
Research Notes of the AAS, 2020, 4, 10, 179
Publication Type :
Report
Accession number :
edsarx.2010.11280
Document Type :
Working Paper
Full Text :
https://doi.org/10.3847/2515-5172/abc01a