surveyed areas of the sky.

AGIS itself does not have the means to decide whether or not a source is a QSO.

Such a selection requires further analysis of the Gaia astrometry and photometry combined.

The DPAC therefore also carries out a number of data analysis tasks that, on the one hand, provide higher level scientific data products (such as source astrophysical parameters or variable star characterisation) and, on the other hand, serve to refine the astrometric, photometric, and spectroscopic processing (e.g. by properly treating binaries or providing a clean selection of QSOs for reference-frame alignment).

The following cyclic processing tasks provide this higher level data analysis:
Non-single-star (NSS) treatment This pipeline (Pourbaix 2011) provides a sophisticated treatment of all binary or multiple sources, including exoplanets.

The astrometric data for any source that is found not to conform to the single-star source model will be treated with source models of increasing complexity, varying from the addition of a perspectiveacceleration term to the derivation of orbital parameters for astrometric binaries.

This pipeline, in addition, deals with resolved double or multiple stars and the astrophysical characterisation of eclipsing binaries.

Solar system object (SSO) treatment This pipeline (Tanga & Mignard 2012) treats the Gaia data for solar system objects, primarily from the main asteroid belt.

Orbital elements of known and newly discovered asteroids are determined, and their spectro-photometric properties are derived from the AF and BP/RP photometry.

The results will also include mass measurements for the ∼100 largest asteroids, direct size measurements for some 1000 asteroids, parametrised shapes, spin periods, and surface-scattering properties for some 10 000 asteroids (Cellino et al. 2015), and taxonomic classifications from the BP/RP photometry.

Source environment analysis (SEA) This task (Harrison 2011) performs a combined analysis of all the SM and AF images collected over the mission lifetime for a given source.

A stacking of the images allows a slightly deeper survey of the surroundings of each source and in particular enables the Article number, page 23 of 36 identification of neighbouring sources that are not visible in the individual images.

The non-trivial aspect of the task is the combination of one-dimensional images obtained at different scan angles across a source.

The results will be used to refine the astrometric and photometric processing (by taking into account potentially disturbing sources near a target source) and will also feed into the non-single-star treatment and the treatment of extended objects described below.

Extended object (EO) analysis This task treats all sources that are considered to be extended, such as galaxies or the cores thereof, and attempts to morphologically classify the sources and to quantify their morphology.

This task also analyses all sources that are classified as QSOs to look, for example, for features that could prevent a QSO from being used as a source for the reference-frame alignment (e.g. host galaxy or lensing effects).

More details can be found in Krone-Martins et al. (2013).

Variable star analysis The Gaia survey will naturally produce a photometric time series for each source spanning the lifetime of the mission and containing some 70–80 observations on average (Sect. 8.1).

The variable star processing takes all the epoch photometry and, for sources showing photometric variability, provides a classification of the variable type and a quantitative characterisation of the light curve.

An overview of the variable star processing can be found in Eyer et al. (2014).

The treatment of variable stars for Gaia DR1 is described in Eyer et al. (2016) and Clementini et al. (2016).

Astrophysical parameter inference This system analyses the combination of astrometry, photometry, and spectroscopy from Gaia to derive discrete source classifications and infer the astrophysical properties of the sources.

The source classification distinguishes single stars, white dwarfs, binaries, quasars, and galaxies, with the quasar selection feeding back into the astrometric processing as described above.

The astrophysical parameters derived from the BP/RP data for stars are the effective temperature, surface gravity, metallicity, and extinction.

From the RVS spectra of the brightest stars, αelement enhancements and individual elemental abundances can additionally be derived.

Descriptions of the status of this system can be found in Bailer-Jones et al. (2013) and Recio-Blanco et al. (2016).

All the results from the analysis tasks above will also be published as part of the Gaia data releases, thus complementing the basic astrometry, photometry, and spectroscopy to provide a rich data set, ready for exploitation by the astronomical community.

Moreover, these analysis tasks feed back into the preceding processing steps and thus provide an essential and strong internal quality control of the DPAC results.