J/A+A/652/A76 Gaia Photometric Science Alerts (Hodgkin+, 2021)
Gaia Photometric Science Alerts.
Hodgkin S.T., Harrison D.L., Breedt E., Wevers T., Rixon G., Delgado A.,
Yoldas A., Kostrzewa-Rutkowska Z., Wyrzykowski L., van Leeuwen M.,
Blagorodnova N., Campbell H., Eappachen D., Fraser M., Ihanec N.,
Koposov S.E., KruszyNska K., Marton G., Rybicki K.A., Brown A.G.A.,
Burgess P.W., Busso G., Cowell S., De Angeli F., Diener C., Evans D.W.,
Gilmore G., Holland G., Jonker P.G., van Leeuwen F., Mignard F.,
Osborne P.J., Portell J., Prusti T., Richards P.J., Riello M.,
Seabroke G.M., Walton N.A., Abraham P., Altavilla G., Baker S.G.,
Bastian U., O'Brien P., de Bruijne J., Butterley T., Carrasco J.M.,
Castaneda J., Clark J.S., Clementini G., Copperwheat C.M., Cropper M.,
Damljanovic G., Davidson M., Davis C.J., Dennefeld M., Dhillon V.S.,
Dolding C., Dominik M., Esquej P., Eyer L., Fabricius C., Fridman M.,
Froebrich D., Garralda N., Gomboc A., Gonzalez-Vidal J.J., Guerra R.,
Hambly N.C., Hardy L.K., Holl B., Hourihane A., Japelj J., Kann D.A.,
Kiss C., Knigge C., Kolb U., Komossa S., Kospal A., Kovacs G., Kun M.,
Leto G., Lewis F., Littlefair S.P., Mahabal A.A., Mundell C.G., Nagy Z.,
Padeletti D., Palaversa L., Pigulski A., Pretorius M.L., van Reeven W.,
Ribeiro V.A.R.M., Roelens M., Rowell N., Schartel N., Scholz A.,
Schwope A., Sipoecz B.M., Smartt S.J., Smith M.D., Serraller I.,
Steeghs D., Sullivan M., Szabados L., Szegedi-Elek E., Tisserand P.,
Tomasella L., van Velzen S., Whitelock P.A., Wilson R.W., Young D.R.
<Astron. Astrophys. 652, A76 (2021)>
=2021A&A...652A..76H 2021A&A...652A..76H (SIMBAD/NED BibCode)
ADC_Keywords: Stars, variable ; Supernovae
Keywords: surveys - supernovae: general - quasars: general -
stars: variables: general
Abstract:
Since July 2014, the Gaia mission has been engaged in a high-spatial-
resolution, time-resolved, precise, accurate astrometric, and
photometric survey of the entire sky. We present the Gaia Science
Alerts project, which has been in operation since 1 June 2016. We
describe the system which has been developed to enable the discovery
and publication of transient photometric events as seen by Gaia. We
outline the data handling, timings, and performances, and we describe
the transient detection algorithms and filtering procedures needed to
manage the high false alarm rate. We identify two classes of events:
(1) sources which are new to Gaia and (2) Gaia sources which have
undergone a significant brightening or fading. Validation of the Gaia
transit astrometry and photometry was performed, followed by testing
of the source environment to minimise contamination from Solar System
objects, bright stars, and fainter near-neighbours. We show that the
Gaia Science Alerts project suffers from very low contamination, that
is there are very few false- positives. We find that the external
completeness for supernovae, CE=0.46, is dominated by the Gaia
scanning law and the requirement of detections from both
fields-of-view. Where we have two or more scans the internal
completeness is CI=0.79 at 3 arcsec or larger from the centres of
galaxies, but it drops closer in, especially within 1 arcsec. The
per-transit photometry for Gaia transients is precise to 1 per cent at
G=13, and 3 per cent at G=19. The per- transit astrometry is accurate
to 55 milliarcseconds when compared to Gaia DR2. The Gaia Science
Alerts project is one of the most homogeneous and productive transient
surveys in operation, and it is the only survey which covers the whole
sky at high spatial resolution (subarcsecond), including the Galactic
plane and bulge.
Description:
JResults of binary classification for Gaia Science Alerts to
distinguish between two classes of Galactic transient: young stellar
objects (YSOs), and cataclysmic variables (CVs). The classifier
employs a support vector machine (SVM), using the standard radial
basis function (RBF) kernel in the scikit-learn package in Python.
Probabilistic output was obtained through 5-fold cross-validation. We
used a set of classified YSOs and CVs as a training set and predicted
classifications for 1815 unknown alerts that have a counterpart in
DR2. For a classification probability, P>0.95, we have classified 638
sources as new CVs, and 202 sources as new YSOs. We caution that this
is a very simplistic classifier which uses only the magnitude, colour
and parallax of the transients. This classifier also only considers
two types of objects, so the list may be contaminated with a small
number of other objects such as flare stars, variable stars or QSOs.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
svmclass.dat 86 840 Results of binary classification for Gaia Science
Alerts to distinguish between two classes of
Galactic transient: young stellar objects (YSOs),
and cataclysmic variables (CVs).
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See also:
I/345 : Gaia DR2 (Gaia Collaboration, 2018)
Byte-by-byte Description of file: svmclass.dat
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Bytes Format Units Label Explanations
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1- 9 A9 --- Name Alert Name (GaiaNNaaa)
11- 29 I19 --- GaiaDR2 DR2 source_id
31- 39 F9.5 deg RAdeg [0.29/359.65] Right ascension (ICRS)
at Ep=2015.5
41- 49 F9.5 deg DEdeg [-89.26/85.48] Declination (ICRS)
at Ep=2015.5
51- 56 F6.4 mas plx [0.0/9.09] Parallax (from DR2)
58- 63 F6.4 mas e_plx [0.02/3.09] Parallax error
65- 73 F9.6 mag Gmag [14.44/20.85] Gaia G-band mean magnitude
(from DR2)
75- 82 F8.6 mag BP-RP [0.02/3.53] Gaia BP-RP colour (from DR2)
84- 86 A3 --- SVMclass [YSO CV] Predicted class (1)
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Note (1): Predicted classes as follows:
YSO = young stellar object
CV = cataclysmic variable
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Acknowledgements:
Simon Hodgkin, sth(at)ast.cam.ac.uk
(End) Patricia Vannier [CDS] 25-Jul-2021