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Gaia Early Data Release 3 : Building the Gaia DR3 source list - Cross-match of Gaia observations

Torra, F. ; Castañeda, J. ; Fabricius, C. ; Lindegren, L. LU orcid ; Clotet, M. ; González-Vidal, J. J. ; Bartolomé, S. ; Bastian, U. ; Bernet, M. and Biermann, M. , et al. (2021) In Astronomy and Astrophysics 649.
Abstract

Context. The Gaia Early Data Release 3 (Gaia EDR3) contains results derived from 78 billion individual field-of-view transits of 2.5 billion sources collected by the European Space Agency's Gaia mission during its first 34 months of continuous scanning of the sky. Aims. We describe the input data, which have the form of onboard detections, and the modeling and processing that is involved in cross-matching these detections to sources. For the cross-match, we formed clusters of detections that were all linked to the same physical light source on the sky. Methods. As a first step, onboard detections that were deemed spurious were discarded. The remaining detections were then preliminarily associated with one or more sources in the existing... (More)

Context. The Gaia Early Data Release 3 (Gaia EDR3) contains results derived from 78 billion individual field-of-view transits of 2.5 billion sources collected by the European Space Agency's Gaia mission during its first 34 months of continuous scanning of the sky. Aims. We describe the input data, which have the form of onboard detections, and the modeling and processing that is involved in cross-matching these detections to sources. For the cross-match, we formed clusters of detections that were all linked to the same physical light source on the sky. Methods. As a first step, onboard detections that were deemed spurious were discarded. The remaining detections were then preliminarily associated with one or more sources in the existing source list in an observation-to-source match. All candidate matches that directly or indirectly were associated with the same source form a match candidate group. The detections from the same group were then subject to a cluster analysis. Each cluster was assigned a source identifier that normally was the same as the identifiers from Gaia DR2. Because the number of individual detections is very high, we also describe the efficient organising of the processing. Results. We present results and statistics for the final cross-match with particular emphasis on the more complicated cases that are relevant for the users of the Gaia catalogue. We describe the improvements over the earlier Gaia data releases, in particular for stars of high proper motion, for the brightest sources, for variable sources, and for close source pairs.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Astrometry, Astronomical databases, Catalogs, Methods: analytical, Methods: data analysis, Space vehicles: instruments
in
Astronomy and Astrophysics
volume
649
article number
A10
publisher
EDP Sciences
external identifiers
  • scopus:85104980298
ISSN
0004-6361
DOI
10.1051/0004-6361/202039637
language
English
LU publication?
yes
id
d1ec3bcb-d416-4004-a817-91a7c36716fd
date added to LUP
2021-05-11 14:57:04
date last changed
2024-04-20 06:00:00
@article{d1ec3bcb-d416-4004-a817-91a7c36716fd,
  abstract     = {{<p>Context. The Gaia Early Data Release 3 (Gaia EDR3) contains results derived from 78 billion individual field-of-view transits of 2.5 billion sources collected by the European Space Agency's Gaia mission during its first 34 months of continuous scanning of the sky. Aims. We describe the input data, which have the form of onboard detections, and the modeling and processing that is involved in cross-matching these detections to sources. For the cross-match, we formed clusters of detections that were all linked to the same physical light source on the sky. Methods. As a first step, onboard detections that were deemed spurious were discarded. The remaining detections were then preliminarily associated with one or more sources in the existing source list in an observation-to-source match. All candidate matches that directly or indirectly were associated with the same source form a match candidate group. The detections from the same group were then subject to a cluster analysis. Each cluster was assigned a source identifier that normally was the same as the identifiers from Gaia DR2. Because the number of individual detections is very high, we also describe the efficient organising of the processing. Results. We present results and statistics for the final cross-match with particular emphasis on the more complicated cases that are relevant for the users of the Gaia catalogue. We describe the improvements over the earlier Gaia data releases, in particular for stars of high proper motion, for the brightest sources, for variable sources, and for close source pairs. </p>}},
  author       = {{Torra, F. and Castañeda, J. and Fabricius, C. and Lindegren, L. and Clotet, M. and González-Vidal, J. J. and Bartolomé, S. and Bastian, U. and Bernet, M. and Biermann, M. and Garralda, N. and Gúrpide, A. and Lammers, U. and Portell, J. and Torra, J.}},
  issn         = {{0004-6361}},
  keywords     = {{Astrometry; Astronomical databases; Catalogs; Methods: analytical; Methods: data analysis; Space vehicles: instruments}},
  language     = {{eng}},
  publisher    = {{EDP Sciences}},
  series       = {{Astronomy and Astrophysics}},
  title        = {{Gaia Early Data Release 3 : Building the Gaia DR3 source list - Cross-match of Gaia observations}},
  url          = {{http://dx.doi.org/10.1051/0004-6361/202039637}},
  doi          = {{10.1051/0004-6361/202039637}},
  volume       = {{649}},
  year         = {{2021}},
}