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.

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 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 -a realisation of the Tycho-Gaia Astrometric Solution (TGAS) -and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr −1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr −1 . For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.

Context. Gaia is Europe's space astrometry mission, aiming to make a three-dimensional map of 1000 million stars in our Milky Way to unravel its kinematical, dynamical, and chemical structure and evolution.Aims. We present a study of Gaia's detection capability of objects, in particular non-saturated stars, double stars, unresolved external galaxies, and asteroids. Gaia's on-board detection software autonomously discriminates stars from spurious objects like cosmic rays and solar protons. For this, parametrised criteria of the shape of the point spread function are used, which need to be calibrated and tuned. This study aims to provide an optimum set of parameters for these filters. Methods. We developed a validated emulation of the on-board detection software, which has 20 free, so-called rejection parameters which govern the boundaries between stars on the one hand and sharp (high-frequency) or extended (low-frequency) events on the other hand. We evaluate the detection and rejection performance of the algorithm using catalogues of simulated single stars, resolved and unresolved double stars, cosmic rays, solar protons, unresolved external galaxies, and asteroids. Results. We optimised the rejection parameters, improving -with respect to the functional baseline -the detection performance of single stars and of unresolved and resolved double stars, while, at the same time, improving the rejection performance of cosmic rays and of solar protons. The optimised rejection parameters also remove the artefact of the functional-baseline parameters that the reduction of the detection probability of stars as a function of magnitude already sets in before the nominal faint-end threshold at G = 20 mag. We find, as a result of the rectangular pixel size, that the minimum separation to resolve a close, equal-brightness double star is 0.23 arcsec in the along-scan and 0.70 arcsec in the across-scan direction, independent of the brightness of the primary. To resolve double stars with ∆G > 0 mag, larger separations are required. We find that, whereas the optimised rejection parameters have no significant impact on the detectability of pure de Vaucouleurs profiles, they do significantly improve the detection of pure exponential-disk profiles, and hence also the detection of unresolved external galaxies with intermediate profiles. We also find that the optimised rejection parameters provide detection gains for asteroids fainter than 20 mag and for fast-moving near-Earth objects fainter than 18 mag, although this gain comes at the expense of a modest detection-probability loss for bright, fast-moving near-Earth objects. The major side effect of the optimised parameters is that spurious ghosts in the wings of bright stars essentially pass unfiltered.

We present Spitzer follow-up imaging of 95 candidate extremely cold brown dwarfs discovered by the Backyard Worlds: Planet 9 citizen science project, which uses visually perceived motion in multiepoch Wide-field Infrared Survey Explorer (WISE) images to identify previously unrecognized substellar neighbors to the Sun. We measure Spitzer [3.6]-[4.5] color to phototype our brown dwarf candidates, with an emphasis on pinpointing the coldest and closest Y dwarfs within our sample. The combination of WISE and Spitzer astrometry provides quantitative confirmation of the transverse motion of 75 of our discoveries. Nine of our motion-confirmed objects have best-fit linear motions larger than 1″ yr −1 ; our fastest-moving discovery is WISEA J155349.96+693355.2 (μ ≈ 2 15 yr −1), a possible T-type subdwarf. We also report a newly discovered wide-separation (∼400 au) T8 comoving companion to the white dwarf LSPM J0055+5948 (the fourth such system to be found), plus a candidate late T companion to the white dwarf LSR J0002+6357 at 5 5 projected separation (∼8700 au if associated). Among our motion-confirmed targets, five have Spitzer colors most consistent with spectral type Y. Four of these five have exceptionally red Spitzer colors suggesting types of Y1 or later, adding considerably to the small sample of known objects in this especially valuable low-temperature regime. Our Y dwarf candidates begin bridging the gap between the bulk of the Y dwarf population and the coldest known brown dwarf.