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W

W. van Reeven

Researcher at European Space Agency

Publications -  37
Citations -  14075

W. van Reeven is an academic researcher from European Space Agency. The author has contributed to research in topics: Astrometry & Stars. The author has an hindex of 19, co-authored 28 publications receiving 10539 citations. Previous affiliations of W. van Reeven include INAF & Paris Diderot University.

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The Gaia mission

T. Prusti, +624 more
TL;DR: Gaia as discussed by the authors is a cornerstone mission in the science programme of the European Space Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach.
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Gaia Data Release 1 Summary of the astrometric, photometric, and survey properties

Anthony G. A. Brown, +590 more
TL;DR: The first Gaia data release, Gaia DR1 as discussed by the authors, consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues.
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Gaia Data Release 2: The astrometric solution

Lennart Lindegren, +92 more
TL;DR: In this article, the authors describe the input data, models, and processing used for the astrometric content of Gaia DR2, and the validation of these results performed within the ASTR task.
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Gaia Data Release 1 - Astrometry: one billion positions, two million proper motions and parallaxes

Lennart Lindegren, +83 more
TL;DR: Gaia Data Release 1 (Gaia DR1) as discussed by the authors contains a large amount of data collected by the Gaia satellite during the first 14 months of its operational phase, including positions, parallaxes, and proper motions to Hipparcos-type precision or better.
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Gaia Data Release 2. Observations of solar system objects

Federica Spoto, +501 more
TL;DR: In this paper, the authors describe the processing of the Gaia DR2 data, and describe the criteria used to select the sample published in Gaia DR 2, and explore the data set to assess its quality.