The miniJPAS survey quasar selection - I. Mock catalogues for classification

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Queiroz, Carolina ; Abramo, L. Raul ; Rodrigues, Natalia V. N. ; Perez-Rafols, Ignasi ; Martinez-Solaeche, Gines ; Hernan-Caballero, Antonio ; Hernandez-Monteagudo, Carlos ; Lumbreras-Calle, Alejandro ; Pieri, Matthew M. ; Morrison, Sean S. ; Bonoli, Silvia ; Chaves-Montero, Jonas ; Chies-Santos, Ana L. ; Diaz-Garcia, L. A. ; Fernandez-Soto, Alberto ; Gonzalez Delgado, Rosa M. ; Alcaniz, Jailson ; Benitez, Narciso ; Javier Cenarro, A. ; Civera, Tamara ; Dupke, Renato A. ; Ederoclite, Alessandro ; Lopez-Sanjuan, Carlos ; Marin-Franch, Antonio ; Mendes de Oliveira, Claudia ; Moles, Mariano ; Muniesa, David ; Sodre Jr, Laerte ; Taylor, Keith ; Varela, Jesus ; Vazquez Ramio, Hector

• Tipo de documento: Artigo Científico
• Fonte: Monthly Notices of the Royal Astronomical Society; v. 520, n. 3, p. 18-pg., 2023-02-15.

Resumo

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper, we develop a pipeline to compute synthetic photometry of quasars, galaxies, and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range 17.5 <= r < 24, we augment our sample of available spectra by shifting the original r-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modelling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys. (AU)

• Processo FAPESP: 15/11442-0 - Quasares e galáxias como traçadores das estruturas em grandes escalas
• Beneficiário: Carolina Queiroz de Abreu Silva
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 19/06766-1 - Seleção de candidatos a quasares com fotometria em multi-bandas
• Beneficiário: Carolina Queiroz de Abreu Silva
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
• Processo FAPESP: 19/10923-5 - Ferramentas de inteligência artificial para grandes levantamentos de galáxias
• Beneficiário: Laerte Sodré Junior
• Modalidade de apoio: Auxílio à Pesquisa - Regular