Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey - I: Catalogue preparation and systematic mitigation

We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343 708 objects in the redshift range 0.8 < z < 2.2 and 72 667 objects with redshifts 2.2 < z <...

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Detalles Bibliográficos
Autores: Rezaie, Mehdi, Ross, Ashley J., Seo, Hee-Jong, Mueller, Eva-Maria, Percival, Will J., Merz, Grant, Katebi, Reza, Bunescu, Razvan C., Bautista, Julian, Brownstein, Joel R., Burtin, Etienne, Dawson, Kyle, Gil-Marín, Héctor, Hou, Jiamin, Lyke, Eleanor B., Macorra, Axel de la, Rossi, Graziano, Schneider, Donald P., Zarrouk, Pauline, Zhao, Gong-Bo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/261311
Acceso en línea:http://hdl.handle.net/10261/261311
Access Level:acceso abierto
Palabra clave:Inflation
Large-scale structure of the universe
Descripción
Sumario:We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343 708 objects in the redshift range 0.8 < z < 2.2 and 72 667 objects with redshifts 2.2 < z < 3.5, covering an effective area of 4699, deg2. We develop a neural network-based approach to mitigate spurious fluctuations in the density field caused by spatial variations in the quality of the imaging data used to select targets for follow-up spectroscopy. Simulations are used with the same angular and radial distributions as the real data to estimate covariance matrices, perform error analyses, and assess residual systematic uncertainties. We measure the mean density contrast and cross-correlations of the eBOSS quasars against maps of potential sources of imaging systematics to address algorithm effectiveness, finding that the neural network-based approach outperforms standard linear regression. Stellar density is one of the most important sources of spurious fluctuations, and a new template constructed using data from the Gaia spacecraft provides the best match to the observed quasar clustering. The end-product from this work is a new value-added quasar catalogue with the improved weights to correct for non-linear imaging systematic effects, which will be made public. Our quasar catalogue is used to measure the local-type primordial non-Gaussianity in a companion paper.

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