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A photometric catalogue of quasars and other point sources in the Sloan Digital Sky Survey

Authors

  • Sheelu Abraham,

    Corresponding author
    1. St Thomas College, Kozhencheri 689641, India
      E-mail: sheeluabraham@gmail.com (SA); nspp@iucaa.ernet.in (NSP); akk@iucaa.ernet.in (AK); yogesh@ncra.tifr.res.in (YGW); sinharita@gmail.com (RS)
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  • Ninan Sajeeth Philip,

    Corresponding author
    1. St Thomas College, Kozhencheri 689641, India
      E-mail: sheeluabraham@gmail.com (SA); nspp@iucaa.ernet.in (NSP); akk@iucaa.ernet.in (AK); yogesh@ncra.tifr.res.in (YGW); sinharita@gmail.com (RS)
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  • Ajit Kembhavi,

    Corresponding author
    1. Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411007, India
      E-mail: sheeluabraham@gmail.com (SA); nspp@iucaa.ernet.in (NSP); akk@iucaa.ernet.in (AK); yogesh@ncra.tifr.res.in (YGW); sinharita@gmail.com (RS)
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  • Yogesh G. Wadadekar,

    Corresponding author
    1. National Centre for Radio Astrophysics, TIFR, Post Bag 3, Ganeshkhind, Pune 411007, India
      E-mail: sheeluabraham@gmail.com (SA); nspp@iucaa.ernet.in (NSP); akk@iucaa.ernet.in (AK); yogesh@ncra.tifr.res.in (YGW); sinharita@gmail.com (RS)
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  • Rita Sinha

    Corresponding author
    1. Elviraland 194, 2591 GM The Hague, the Netherlands
      E-mail: sheeluabraham@gmail.com (SA); nspp@iucaa.ernet.in (NSP); akk@iucaa.ernet.in (AK); yogesh@ncra.tifr.res.in (YGW); sinharita@gmail.com (RS) Formerly with Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411007, India.
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E-mail: sheeluabraham@gmail.com (SA); nspp@iucaa.ernet.in (NSP); akk@iucaa.ernet.in (AK); yogesh@ncra.tifr.res.in (YGW); sinharita@gmail.com (RS)

Formerly with Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411007, India.

ABSTRACT

We present a catalogue of about six million unresolved photometric detections in the Sloan Digital Sky Survey (SDSS) Seventh Data Release, classifying them into stars, galaxies and quasars. We use a machine learning classifier trained on a subset of spectroscopically confirmed objects from 14th to 22nd magnitude in the SDSS i band. Our catalogue consists of 2 430 625 quasars, 3 544 036 stars and 63 586 unresolved galaxies from 14th to 24th magnitude in the SDSS i band. Our algorithm recovers 99.96 per cent of spectroscopically confirmed quasars and 99.51 per cent of stars to i ∼ 21.3 in the colour window that we study. The level of contamination due to data artefacts for objects beyond i = 21.3 is highly uncertain and all mention of completeness and contamination in the paper are valid only for objects brighter than this magnitude. However, a comparison of the predicted number of quasars with the theoretical number counts shows reasonable agreement.

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