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

Journal Article · · Monthly Notices of the Royal Astronomical Society
 [1];  [2];  [2];  [3];  [4];  [5];  [6];  [5];  [7];  [8];  [9];  [10];  [11];  [4];  [12];  [4];  [13];  [4];  [5];  [5] more »;  [14];  [5];  [5];  [5];  [2];  [15];  [5];  [2];  [16];  [5];  [5] « less
  1. Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil); Universidade de São Paulo (Brazil)
  2. Universidade de São Paulo (Brazil)
  3. Centre National de la Recherche Scientifique (CNRS) (France); Sorbonne Univ., Paris (France); University Paris-Diderot (France); Aix-Marseille Univ., Marseille (France)
  4. Consejo Superior de Investigaciones Cientificas (CSIC), Granada (Spain). Instituto de Astrofísica de Andalucía
  5. Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Teruel (Spain)
  6. Univ. of La Laguna (Spain); Instituto de Astrofísica de Canarias, La Laguna (Spain)
  7. Centre National de la Recherche Scientifique (CNRS) (France); Aix-Marseille Univ., Marseille (France)
  8. Centre National de la Recherche Scientifique (CNRS) (France); Aix-Marseille Univ., Marseille (France); Univ. of Illinois at Urbana-Champaign, IL (United States)
  9. Donostia International Physics Center (DIPC), San Sebastian (Spain); Basque Foundation for Science, Bilbao (Spain). IKERBASQUE
  10. Donostia International Physics Center (DIPC), San Sebastian (Spain)
  11. Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil); Chinese Academy of Sciences (CAS), Shanghai (China). Shanghai Astronomical Observatory
  12. Inst. of Physics, Cantabria (Spain); Univ. of Valencia (Spain)
  13. Observatório Nacional, Rio de Janeiro (Brazil)
  14. Observatório Nacional, Rio de Janeiro (Brazil); Univ. of Michigan, Ann Arbor, MI (United States); Univ. of Alabama, Tuscaloosa, AL (United States)
  15. Consejo Superior de Investigaciones Cientificas (CSIC), Granada (Spain). Instituto de Astrofísica de Andalucía; Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Teruel (Spain)
  16. Instruments, La Canada Flintridge, CA (United States)
+ Show Author Affiliations
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.
Research Organization:
US Department of Energy (USDOE), Washington, DC (United States). Office of Science, Sloan Digital Sky Survey (SDSS)
Sponsoring Organization:
CNPq; French National Research Agency (ANR); Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); MCIU; Spanish Ministry of Science and Innovation
OSTI ID:
2425348
Journal Information:
Monthly Notices of the Royal Astronomical Society, Journal Name: Monthly Notices of the Royal Astronomical Society Journal Issue: 3 Vol. 520; ISSN 0035-8711; ISSN 1365-2966
Publisher:
Oxford University PressCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

79 ASTRONOMY AND ASTROPHYSICS
catalogues
methods: data analysis
quasars: general
surveys
techniques: photometric