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.

We present results of the analysis of 70 RR Lyrae stars located in the bar of the Large Magellanic Cloud (LMC). Combining spectroscopically determined metallicity of these stars from the literature with precise periods from the OGLE III catalogue and multi-epoch K s photometry from the VISTA survey of the Magellanic Clouds system (VMC), we derive a new near-infrared period-luminosity-metallicity (PL K s Z) relation for RR Lyrae variables. In order to fit the relation we use a fitting method developed specifically for this study. The zero-point of the relation is estimated in two different ways: by assuming the value of the distance to the LMC and by using Hubble Space Telescope (HST) parallaxes of five RR Lyrae stars in the Milky Way (MW). The difference in distance moduli derived by applying these two approaches is ∼ 0.2 mag. To investigate this point further we derive the PL K s Z relation based on 23 MW RR Lyrae stars which had been analysed in Baade-Wesselink studies. We compared the derived PL K s Z relations for RR Lyrae stars in the MW and LMC. Slopes and zero-points are different, but still consistent within the errors. The shallow slope of the metallicity term is confirmed by both LMC and MW variables. The astrometric space mission Gaia is expected to provide a huge contribution to the determination of the RR Lyrae PL K s Z relation, however, calculating an absolute magnitude from the trigonometric parallax of each star and fitting a PL K s Z relation directly to period and absolute magnitude leads to biased results. We present a tool to achieve an unbiased solution by modelling the data and inferring the slope and zero-point of the relation via statistical methods.

We present results from the analysis of 2997 fundamental mode RR Lyrae variables located in the Small Magellanic Cloud (SMC). For these objects near-infrared timeseries photometry from the VISTA survey of the Magellanic Clouds system (VMC) and visual light curves from the OGLE IV survey are available. In this study the multi-epoch K s -band VMC photometry was used for the first time to derive intensityaveraged magnitudes of the SMC RR Lyrae stars. We determined individual distances to the RR Lyrae stars from the near-infrared period-absolute magnitude-metallicity (P M Ks Z) relation, which has a number of advantages in comparison with the visual absolute magnitude-metallicity (M V − [Fe/H]) relation, such as a smaller dependence of the luminosity on interstellar extinction, evolutionary effects and metallicity. The distances we have obtained were used to study the three-dimensional structure of the SMC. The distribution of the SMC RR Lyrae stars is found to be ellipsoidal. The actual line-of-sight depth of the SMC is in the range from 1 to 10 kpc, with an average depth of 4.3 ± 1.0 kpc. We found that RR Lyrae stars in the eastern part of the SMC are affected by interactions of the Magellanic Clouds. However, we do not see a clear bimodality in the distribution of RR Lyrae stars as observed for red clump (RC) stars.

Aims. An effort has been made to simulate the expected Gaia Catalogue, including the effect of observational errors. We statistically analyse this simulated Gaia data to better understand what can be obtained from the Gaia astrometric mission. This catalogue is used to investigate the potential yield in astrometric, photometric, and spectroscopic information and the extent and effect of observational errors on the true Gaia Catalogue. This article is a follow-up to previous work, where the expected Gaia Catalogue content was reviewed but without the simulation of observational errors. Methods. We analysed the Gaia Object Generator (GOG) catalogue using the Gaia Analysis Tool (GAT), thereby producing a number of statistics about the catalogue. Results. A simulated catalogue of one billion objects is presented, with detailed information on the 523 million individual single stars it contains. Detailed information is provided for the expected errors in parallax, position, proper motion, radial velocity, and the photometry in the four Gaia bands. Information is also given on the expected performance of physical parameter determination, including temperature, metallicity, and line-of-sight extinction.