Статья

Angular clustering properties of the DESI QSO target selection using DR9 Legacy Imaging Surveys

E. ChaussidonIRFU - Institut de Recherches sur les lois Fondamentales de l'Univers (CEA Saclay F-91191 Gif sur Yvette cedex - France)Christophe YècheIRFU - Institut de Recherches sur les lois Fondamentales de l'Univers (CEA Saclay F-91191 Gif sur Yvette cedex - France)N. Palanque‐DelabrouilleIRFU - Institut de Recherches sur les lois Fondamentales de l'Univers (CEA Saclay F-91191 Gif sur Yvette cedex - France)Arnaud de MattiaIRFU - Institut de Recherches sur les lois Fondamentales de l'Univers (CEA Saclay F-91191 Gif sur Yvette cedex - France)Adam D. MyersDepartment of Physics and Astronomy, University of Wyoming , 1000 E. University Ave., Laramie, WY 82071, USAMehdi RezaieDepartment of Physics and Astronomy, Ohio University , Athens, OH 45701, USAA.J. RossCenter of Cosmology and AstroParticle Physics, The Ohio State University , Columbus, OH 43210, USAHee‐Jong SeoDepartment of Physics and Astronomy, Ohio University , Athens, OH 45701, USADavid BrooksDepartment of Physics and Astronomy, University College London , Gower Street, London WC1E 6BT, UKE. GaztañagaInstitute of Space Sciences (ICE, CSIC), Campus UAB , Carrer de Can Magrans sn, E-08193 Bellaterra, Barcelona, SpainR. KehoeDepartment of Physics, Southern Methodist University, 3215 Daniel Ave., Dallas, TX, 75205, USAM. E. LeviLawrence Berkeley National Laboratory , 1 Cyclotron Road, Berkeley, CA 94720, USAJeffrey A. NewmanDepartment of Physics and Astronomy, University of Pittsburgh , Pittsburgh, PA 15260, USAG. TarléDepartment of Physics, University of Michigan , Ann Arbor, MI 48109, USAKai ZhangLawrence Berkeley National Laboratory , 1 Cyclotron Road, Berkeley, CA 94720, USA

2021en

ABI

Аннотация

The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next five years. The aim of this work is to validate the quasar selection by studying the impact of imaging systematics as well as stellar and galactic contaminants, and to develop a procedure to mitigate them. Density fluctuations of quasar targets are found to be related to photometric properties such as seeing and depth of the Data Release 9 of the DESI Legacy Imaging Surveys. To model this complex relation, we explore machine learning algorithms (Random Forest and Multi-Layer Perceptron) as an alternative to the standard linear regression. Splitting the footprint of the Legacy Imaging Surveys into three regions according to photometric properties, we perform an independent analysis in each region, validating our method using eBOSS EZ-mocks. The mitigation procedure is tested by comparing the angular correlation of the corrected target selection on each photometric region to the angular correlation function obtained using quasars from the Sloan Digital Sky Survey (SDSS)Data Release 16. With our procedure, we recover a similar level of correlation between DESI quasar targets and SDSS quasars in two thirds of the total footprint and we show that the excess of correlation in the remaining area is due to a stellar contamination which should be removed with DESI spectroscopic data. We derive the Limber parameters in our three imaging regions and compare them to previous measurements from SDSS and the 2dF QSO Redshift Survey.

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Идентификаторы

DOI: 10.1093/mnras/stab3252

Цитирования и источники

Цитирований: 6Использованных источников: 0

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