Gaia Space Mission
DOI:
https://doi.org/10.47456/Cad.Astro.v3n2.38511Keywords:
Gaia Space Mission, space telescopes, Milk Way, galaxies, astrometryAbstract
With careful and systematic observations of the sky, human beings have been building and refining their knowledge about the Universe and about themselves for a long time. The observational magnitudes on which astronomy rests are finally being measured abundantly and with unimaginable precision thanks to the Gaia Space Mission of the European Space Agency. With its three data releases (2016, 2018 and 2020/22), we have, today, in our hands, observational data in quantity and quality that until very recently we did not even dream of. Among them, the most important greatness of all astronomy: the distance of more than 1.5 billion stars that allows us to say where they are, what they look like and how they ''dance'', thus starting a new era in the study of the Galaxy and the Universe. Universe. This data, made available to the entire world at the same time, represents a radical shift in the astronomical knowledge base and will tremendously impact astronomy in the broadest sense of the term, for many, many years to come. Colleagues from all over the world are immersed in this ocean of positions, movements, brightness, colors, etc., confirming, reviewing and refining what we know and about to face, once again in history, the new.
Downloads
References
Gaia Collaboration et al., The Gaia mission, Astronomy & Astrophysics 595, A1 (2016). ArXiv:1609.04153.
Gaia Collaboration et al., Gaia data release 1 - summary of the astrometric, photometric, and survey properties, A&A 595, A2 (2016).
A. G. Brown, Microarcsecond astrometry: Science highlights from Gaia, Annual Review of Astronomy and Astrophysics 59(1), 59 (2021).
Gaia Collaboration et al., Gaia Data Release 2. Summary of the contents and survey properties, Astronomy & Astrophysics 616, A1 (2018). ArXiv:1804.09365.
Gaia Collaboration et al., Gaia Data Release 2. The celestial reference frame (Gaia-CRF2), Astronomy & Astrophysics 616, A14 (2018). ArXiv:1804.09377.
Gaia Collaboration et al., Gaia Early Data Release 3. Summary of the contents and survey properties, Astronomy & Astrophysics 649, A1 (2021). ArXiv:2012.01533.
Gaia Collaboration et al., Gaia Data Release 3: The extragalactic content (2022). ArXiv: 2206.05681.
Gaia Collaboration et al., Gaia Data Release 3: A golden sample of astrophysical parameters (2022). ArXiv:2206.05870.
Gaia Collaboration et al., Gaia Data Release 3: Reflectance spectra of Solar System small bodies (2022). ArXiv:2206.12174.
C. Ducourant et al., Gaia Data Release 3: Surface brightness profiles of galaxies and host galaxies of quasars (2022). ArXiv: 2206.14491.
P. Tanga et al., Data Release 3: the Solar System survey (2022). ArXiv:2206.05561.
The HIPPARCOS and TYCHO catalogues. Astrometric and photometric star catalogues derived from the ESA HIPPARCOS Space Astrometry Mission, vol. 1200 de ESA Special Publication (ESA Publications Division, 1997).
B. Viateau et al., The Bordeaux and Valinhos CCD meridian circles, Astron. Astrophys. Suppl. Ser. 134, 173 (1999).
L. Lindegren et al., Gaia Data Release 1. Astrometry: One billion positions, two million proper motions and parallaxes, Astronomy & Astrophysics 595, A4 (2016). ArXiv: 1609.04303.
E. Høg et al., The Tycho-2 catalogue of the 2.5 million brightest stars, Astronomy & Astrophysics 355, L27 (2000).
D. Michalik, L. Lindegren e D. Hobbs, The Tycho-Gaia astrometric solution . How to get 2.5 million parallaxes with less than one year of Gaia data, Astronomy & Astrophysics 574, A115 (2015). ArXiv:1412.8770.
A. Krone-Martins, Ampliando horizontes da Missão Espacial Gaia graças à análise de objetos extensos, Tese de Doutorado, Universidade de São Paulo e Universitè de Bordeaux I, São Paulo (2011).
A. Krone-Martins et al., Pushing the limits of the Gaia space mission by analyzing galaxy morphology, Astronomy & Astrophysics 556, A102 (2013). ArXiv:1307.5732.
A. Krone-Martinsa et al., Identification of galaxies from the Gaia DR2 – ALLWISE all-sky catalogues with unsupervised machine-learning, submetido ao Astronomy & Astrophysics (2022).
R. E. de Souza et al., Detection of galaxies with Gaia, Astronomy & Astrophysics 568, A124 (2014). ArXiv:1404.4521.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Ramachrisna Teixeira
This work is licensed under a Creative Commons Attribution 4.0 International License.