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VII/285 Gaia DR2 quasar and galaxy classification (Bailer-Jones+, 2019)
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Beginning of ReadMe :VII/285 Gaia DR2 quasar and galaxy classification (Bailer-Jones+, 2019)
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Quasar and galaxy classification in Gaia Data Release 2.
Bailer-Jones C.A.L., Fouesneau M., Andrae R.
<Mon. Not. R. Astron. Soc. 490, 5615-5633 (2019)>
=2019MNRAS.490.5615B
=2019yCat.7285....0B
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ADC_Keywords: Surveys ; QSOs ; Galaxies
Keywords: methods: data analysis - methods: statistical - surveys -
astrometry - galaxies: general - quasars: general
Abstract:
We provide probabilistic quasar and galaxy classifications for 2.7
million sources in Gaia Data Release 2. This has been achieved using a
supervised classification method (Gaussian Mixture Models) based only
on photometric and astrometric data (8 features) in Gaia-DR2. The
model is trained empirically to classify objects into three classes -
star, quasar, galaxy - for all objects with G>=14.5mag down to the
Gaia magnitude limit of G=21.0mag. We provide the probabilities for
being a quasar (pqso) and a galaxy (pgal); the probability of being a
star is pstar = 1-(pqso+pgal), and all other Gaia data can be obtained
by cross-matching Gaia-DR2 using the source identifier. As our main
goal is to identify extragalactic objects, we only report objects with
pqso+pgal>0.5. These probabilities incorporate a sensible class prior,
namely that quasars are 500 times rarer than stars, and that galaxies
7500 times rarer than stars. See the paper for details of the purity
and completeness of samples drawn from this catalogue, and for more
details of its construction, contents, and validation.
Description:
The classes are defined by the supervised training sets used in the
classifier. Galaxies and quasars are identified for the training set
by a cross-match to objects with spectroscopic classifications from
the Sloan Digital Sky Survey. Stars are defined directly from
Gaia-DR2.