Gaia 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. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page.

Aims. The scientific community needs to be prepared to analyse the data from Gaia, one of the most ambitious ESA space missions, which is to be launched in 2012. The purpose of this paper is to provide data and tools to predict how Gaia photometry is expected to be. To do so, we provide relationships among colours involving Gaia magnitudes (white light G, blue G BP , red G RP and G RVS bands) and colours from other commonly used photometric systems (Johnson-Cousins, Sloan Digital Sky Survey, Hipparcos and Tycho). Methods. The most up-to-date information from industrial partners has been used to define the nominal passbands, and based on the BaSeL3.1 stellar spectral energy distribution library, relationships were obtained for stars with different reddening values, ranges of temperatures, surface gravities and metallicities. Results. The transformations involving Gaia and Johnson-Cousins V − I C and Sloan DSS g − z colours have the lowest residuals. A polynomial expression for the relation between the effective temperature and the colour G BP −G RP was derived for stars with T eff ≥ 4500 K. For stars with T eff < 4500 K, dispersions exist in gravity and metallicity for each absorption value in g − r and r − i. Transformations involving two Johnson or two Sloan DSS colours yield lower residuals than using only one colour. We also computed several ratios of total-to-selective absorption including absorption A G in the G band and colour excess E(G BP -G RP ) for our sample stars. A relationship involving A G /A V and the intrinsic (V − I C ) colour is provided. The derived Gaia passbands have been used to compute tracks and isochrones using the Padova and BASTI models. Finally, the performances of the predicted Gaia magnitudes have been estimated according to the magnitude and the celestial coordinates of the star. Conclusions. The provided dependencies among colours can be used for planning scientific exploitation of Gaia data, performing simulations of the Gaia-like sky, planning ground-based complementary observations and for building catalogues with auxiliary data for the Gaia data processing and validation.

Context. We present the early installment of the third Gaia data release, Gaia EDR3, consisting of astrometry and photometry for 1.8 billion sources brighter than magnitude 21, complemented with the list of radial velocities from Gaia DR2. Aims. A summary of the contents of Gaia EDR3 is presented, accompanied by a discussion on the differences with respect to Gaia DR2 and an overview of the main limitations which are present in the survey. Recommendations are made on the responsible use of Gaia EDR3 results. Methods. The raw data collected with the Gaia instruments during the first 34 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium and turned into this early third data release, which represents a major advance with respect to Gaia DR2 in terms of astrometric and photometric precision, accuracy, and homogeneity. Results. Gaia EDR3 contains celestial positions and the apparent brightness in G for approximately 1.8 billion sources. For 1.5 billion of those sources, parallaxes, proper motions, and the (GBP − GRP) colour are also available. The passbands for G, GBP, and GRP are provided as part of the release. For ease of use, the 7 million radial velocities from Gaia DR2 are included in this release, after the removal of a small number of spurious values. New radial velocities will appear as part of Gaia DR3. Finally, Gaia EDR3 represents an updated materialisation of the celestial reference frame (CRF) in the optical, the Gaia-CRF3, which is based solely on extragalactic sources. The creation of the source list for Gaia EDR3 includes enhancements that make it more robust with respect to high proper motion stars, and the disturbing effects of spurious and partially resolved sources. The source list is largely the same as that for Gaia DR2, but it does feature new sources and there are some notable changes. The source list will not change for Gaia DR3. Conclusions. Gaia EDR3 represents a significant advance over Gaia DR2, with parallax precisions increased by 30 per cent, proper motion precisions increased by a factor of 2, and the systematic errors in the astrometry suppressed by 30–40% for the parallaxes and by a factor ~2.5 for the proper motions. The photometry also features increased precision, but above all much better homogeneity across colour, magnitude, and celestial position. A single passband for G, GBP, and GRP is valid over the entire magnitude and colour range, with no systematics above the 1% level