No Arabic abstract
The orbits, atmospheric parameters, chemical abundances, and ages of individual stars in the Milky Way provide the most comprehensive illustration of galaxy formation available. The Tycho-Gaia Astrometric Solution (TGAS) will deliver astrometric parameters for the largest ever sample of Milky Way stars, though its full potential cannot be realized without the addition of complementary spectroscopy. Among existing spectroscopic surveys, the RAdial Velocity Experiment (RAVE) has the largest overlap with TGAS ($gtrsim$200,000 stars). We present a data-driven re-analysis of 520,781 RAVE spectra using The Cannon. For red giants, we build our model using high-fidelity APOGEE stellar parameters and abundances for stars that overlap with RAVE. For main-sequence and sub-giant stars, our model uses stellar parameters from the K2/EPIC. We derive and validate effective temperature $T_{rm eff}$, surface gravity $log{g}$, and chemical abundances of up to seven elements (O, Mg, Al, Si, Ca, Fe, Ni). We report a total of 1,685,851 elemental abundances with a typical precision of 0.07 dex, a substantial improvement over previous RAVE data releases. The synthesis of RAVE-on and TGAS is the most powerful data set for chemo-dynamic analyses of the Milky Way ever produced.
We present part 2 of the 6th and final Data Release (DR6 or FDR) of the Radial Velocity Experiment (RAVE), a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A) and span the complete time frame from the start of RAVE observations on 12 April 2003 to their completion on 4 April 2013. In the second of two publications, we present the data products derived from 518387 observations of 451783 unique stars using a suite of advanced reduction pipelines focussing on stellar atmospheric parameters, in particular purely spectroscopically derived stellar atmospheric parameters (Teff, log(g), and the overall metallicity), enhanced stellar atmospheric parameters inferred via a Bayesian pipeline using Gaia DR2 astrometric priors, and asteroseismically calibrated stellar atmospheric parameters for giant stars based on asteroseismic observations for 699 K2 stars. In addition, we provide abundances of the elements Fe, Al, and Ni, as well as an overall [alpha/Fe] ratio obtained using a new pipeline based on the GAUGUIN optimization method that is able to deal with variable signal-to-noise ratios. The RAVE DR6 catalogs are cross matched with relevant astrometric and photometric catalogs, and are complemented by orbital parameters and effective temperatures based on the infrared flux method. The data can be accessed via the RAVE Web site (http://rave-survey.org) or the Vizier database.
Stellar clusters are important for astrophysics in many ways, for instance as optimal tracers of the Galactic populations to which they belong or as one of the best test bench for stellar evolutionary models. Gaia DR1, with TGAS, is just skimming the wealth of exquisite information we are expecting from the more advanced catalogues, but already offers good opportunities and indicates the vast potentialities. Gaia results can be efficiently complemented by ground-based data, in particular by large spectroscopic and photometric surveys. Examples of some scientific results of the Gaia-ESO survey are presented, as a teaser for what will be possible once advanced Gaia releases and ground-based data will be combined.
Atmospheric parameters determined via spectral modelling are unavailable for many of the known magnetic early B-type stars. We utilized high-resolution spectra together with NLTE models to measure effective temperatures $T_{rm eff}$ and surface gravities $log{g}$ of stars for which these measurements are not yet available. We find good agreement between our $T_{rm eff}$ measurements and previous results obtained both photometrically and spectroscopically. For $log{g}$, our results are compatible with previous spectroscopic measurements; however, surface gravities of stars previously determined photometrically have been substantially revised. We furthermore find that $log{g}$ measurements obtained with HARPSpol are typically about 0.1 dex lower than those from comparable instruments. Luminosities were determined using Gaia Data Release 2 parallaxes. We find Gaia parallaxes to be unreliable for bright stars ($V<6$ mag) and for binaries; in these cases we reverted to Hipparcos parallaxes. In general we find luminosities systematically lower than those previously reported. Comparison of $log{g}$ and $log{L}$ to available rotational and magnetic measurements shows no correlation between either parameter with magnetic data, but a clear slow-down in rotation with both decreasing $log{g}$ and increasing $log{L}$, a result compatible with the expectation that magnetic braking should lead to rapid magnetic spindown that accelerates with increasing mass-loss.
The new data release (DR5) of the RAdial Velocity Experiment (RAVE) includes radial velocities of 520,781 spectra of 457,588 individual stars, of which 215,590 individual stars are released in the Tycho-Gaia astrometric solution (TGAS) in Gaia DR1. Therefore, RAVE contains the largest TGAS overlap of the recent and ongoing Milky Way spectroscopic surveys. Most of the RAVE stars also contain stellar parameters (effective temperature, surface gravity, overall metallicity), as well as individual abundances for Mg, Al, Si, Ca, Ti, Fe, and Ni. Combining RAVE with TGAS brings the uncertainties in space velocities down by a factor of 2 for stars in the RAVE volume -- 10 km/s uncertainties in space velocities are now able to be derived for the majority (70%) of the RAVE-TGAS sample, providing a powerful platform for chemo-dynamic analyses of the Milky Way. Here we discuss the RAVE-TGAS impact on Galactic archaeology as well as how the Gaia parallaxes can be used to break degeneracies within the RAVE spectral regime for an even better return in the derivation of stellar parameters and abundances.
We apply the twin method to determine parallaxes to 232,545 stars of the RAVE survey using the parallaxes of Gaia DR1 as a reference. To search for twins in this large dataset, we apply the t-stochastic neighbour embedding t-SNE projection which distributes the data according to their spectral morphology on a two dimensional map. From this map we choose the twin candidates for which we calculate a chi^2 to select the best sets of twins. Our results show a competitive performance when compared to other model-dependent methods relying on stellar parameters and isochrones. The power of the method is shown by finding that the accuracy of our results is not significantly affected if the stars are normal or peculiar since the method is model free. We find twins for 60% of the RAVE sample which is not contained in TGAS or that have TGAS uncertainties which are larger than 20%. We could determine parallaxes with typical errors of 28%. We provide a complementary dataset for the RAVE stars not covered by TGAS, or that have TGAS uncertainties which are larger than 20%, with model-free parallaxes scaled to the Gaia measurements.