Gaia broad band photometry super([sstarf])

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 sub(BP), red G sub(RP) and G sub(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 sub(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 sub(BP) - G sub(RP) was derived for stars with T sub(eff) greater than or equal to 4500 K. For stars with T sub(eff) < 4500 K, dispersions exist in gravity and metallicity for each absorption value in g - minus; 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 sub(G) in the G band and colour excess E(G sub(BP)-G sub(RP)) for our sample stars. A relationship involving A sub(G) / A sub(V) and the intrinsic (V - I sub(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.