Lindegren, L, Klioner, SA, Hernandez, J, Bombrun, A, Ramos-Lerate, M, Steidelmuller, H, Bastian, U, Biermann, M, de Torres, A, Gerlach, E, Geyer, R, Hilger, T, Hobbs, D, Lammers, U, McMillan, PJ, Stephenson, CA, Castaneda, J, Davidson, M, Fabricius, C, Gracia-Abril, G et al, Portell, J, Rowell, N, Teyssier, D, Torra, F, Bartolome, S, Clotet, M, Garralda, N, Gonzalez-Vidal, JJ, Torra, J, Abbas, U, Altmann, M, Varela, EA, Balaguer-Nunez, L, Balog, Z, Barache, C, Becciani, U, Bernet, M, Bertone, S, Bianchi, L, Bouquillon, S, Brown, AGA, Bucciarelli, B, Busonero, D, Butkevich, AG, Buzzi, R, Cancelliere, R, Carlucci, T, Charlot, P, Cioni, M-RL, Crosta, M, Crowley, C, del Peloso, EF, del Pozo, E, Drimmel, R, Esquej, P, Fienga, A, Fraile, E, Gai, M, Garcia-Reinaldos, M, Guerra, R, Hambly, NC, Hauser, M, Janssen, K, Jordan, S, Kostrzewa-Rutkowska, Z, Lattanzi, MG, Liao, S, Licata, E, Lister, TA, Loffler, W, Marchant, JM, Masip, A, Mignard, F, Mints, A, Molina, D, Mora, A, Morbidelli, R, Murphy, CP, Pagani, C, Panuzzo, P, Esteller, XP, Poggio, E, Re Fiorentin, P, Riva, A, Selles, AS, Gimenez, VS, Sarasso, M, Sciacca, E, Siddiqui, H, Smart, RL, Souami, D, Spagna, A, Steele, IA, Taris, F, Utrilla, E, van Reeven, W and Vecchiato, A (2021) Gaia Early Data Release 3 The astrometric solution. Astronomy & Astrophysics, 649. ISSN 1432-0746

Full text not available from this repository. Please see publisher or open access link below:

Abstract

Context. Gaia Early Data Release 3 (Gaia EDR3) contains results for 1.812 billion sources in the magnitude range G = 3–21 based on observations collected by the European Space Agency Gaia satellite during the first 34 months of its operational phase.

Aims. We describe the input data, the models, and the processing used for the astrometric content of Gaia EDR3, as well as the validation of these results performed within the astrometry task.

Methods. The processing broadly followed the same procedures as for Gaia DR2, but with significant improvements to the modelling of observations. For the first time in the Gaia data processing, colour-dependent calibrations of the line- and point-spread functions have been used for sources with well-determined colours from DR2. In the astrometric processing these sources obtained five-parameter solutions, whereas other sources were processed using a special calibration that allowed a pseudocolour to be estimated as the sixth astrometric parameter. Compared with DR2, the astrometric calibration models have been extended, and the spin-related distortion model includes a self-consistent determination of basic-angle variations, improving the global parallax zero point.

Results. Gaia EDR3 gives full astrometric data (positions at epoch J2016.0, parallaxes, and proper motions) for 1.468 billion sources (585 millionwith five-parameter solutions, 882 million with six parameters), and mean positions at J2016.0 for an additional 344 million.Solutions with five parameters are generally more accurate than six-parameter solutions, and are available for 93% of the sources brighter than the 17th magnitude. The median uncertainty in parallax and annual proper motion is 0.02–0.03 mas at magnitude G = 9–14, and around 0.5 mas at G = 20. Extensive characterisation of the statistical properties of the solutions is provided, including the estimated angular power spectrum of parallax bias from the quasars.

Item Type:	Article
Uncontrolled Keywords:	astrometry; Astronomy & Astrophysics; CATALOG; CORE SOLUTION; FRAMEWORK; methods: data analysis; MODEL; parallaxes; Physical Sciences; proper motions; Science & Technology; space vehicles: instruments; Science & Technology; Physical Sciences; Astronomy & Astrophysics; astrometry; parallaxes; proper motions; methods: data analysis; space vehicles: instruments; CORE SOLUTION; CATALOG; MODEL; FRAMEWORK; Astronomy & Astrophysics; 0201 Astronomical and Space Sciences
Subjects:	Q Science > QB Astronomy
Divisions:	Astrophysics Research Institute
Publisher:	EDP Sciences
SWORD Depositor:	A Symplectic
Date Deposited:	17 Oct 2022 10:12
Last Modified:	17 Oct 2022 10:14
DOI or ID number:	10.1051/0004-6361/202039709
URI:	https://researchonline.ljmu.ac.uk/id/eprint/17849

View Item