The RAdial Velocity Experiment (RAVE) is a medium resolution R~7500 spectroscopic survey of the Milky Way which already obtained over half a million stellar spectra. They present a randomly selected magnitude-limited sample, so it is important to use
a reliable and automated classification scheme which identifies normal single stars and discovers different types of peculiar stars. To this end we present a morphological classification of 350,000 RAVE survey stellar spectra using locally linear embedding, a dimensionality reduction method which enables representing the complex spectral morphology in a low dimensional projected space while still preserving the properties of the local neighborhoods of spectra. We find that the majority of all spectra in the database ~90-95% belong to normal single stars, but there is also a significant population of several types of peculiars. Among them the most populated groups are those of various types of spectroscopic binary and chromospherically active stars. Both of them include several thousands of spectra. Particularly the latter group offers significant further investigation opportunities since activity of stars is a known proxy of stellar ages. Applying the same classification procedure to the sample of normal single stars alone shows that the shape of the projected manifold in two dimensional space correlates with stellar temperature, surface gravity and metallicity.
Repeated spectroscopic observations of stars in the Radial Velocity Experiment (RAVE) database are used to identify and examine single-lined binary (SB1) candidates. The RAVE latest internal database (VDR3) includes radial velocities, atmospheric and
other parameters for approximately quarter million of different stars with little less than 300,000 observations. In the sample of ~20,000 stars observed more than once, 1333 stars with variable radial velocities were identified. Most of them are believed to be SB1 candidates. The fraction of SB1 candidates among stars with several observations is between 10% and 15% which is the lower limit for binarity among RAVE stars. Due to the distribution of time spans between the re-observation that is biased towards relatively short timescales (days to weeks), the periods of the identified SB1 candidates are most likely in the same range. Because of the RAVEs narrow magnitude range most of the dwarf candidates belong to the thin Galactic disk while the giants are part of the thick disk with distances extending to up to a few kpc. The comparison of the list of SB1 candidates to the VSX catalog of variable stars yielded several pulsating variables among the giant population with the radial velocity variations of up to few tens of km/s. There are 26 matches between the catalog of spectroscopic binary orbits (SB9) and the whole RAVE sample for which the given periastron time and the time of RAVE observation were close enough to yield a reliable comparison. RAVE measurements of radial velocities of known spectroscopic binaries are consistent with their published radial velocity curves.
We devise a new method for the detection of double-lined binary stars in a sample of the Radial Velocity Experiment (RAVE) survey spectra. The method is both tested against extensive simulations based on synthetic spectra, and compared to direct visu
al inspection of all RAVE spectra. It is based on the properties and shape of the cross-correlation function, and is able to recover ~80% of all binaries with an orbital period of order 1 day. Systems with periods up to 1 year are still within the detection reach. We have applied the method to 25,850 spectra of the RAVE second data release and found 123 double-lined binary candidates, only eight of which are already marked as binaries in the SIMBAD database. Among the candidates, there are seven that show spectral features consistent with the RS CVn type (solar type with active chromosphere) and seven that might be of W UMa type (over-contact binaries). One star, HD 101167, seems to be a triple system composed of three nearly identical G-type dwarfs. The tested classification method could also be applicable to the data of the upcoming Gaia mission.
Although primarily aimed at the galactic archeology and evolution, automated all-sky spectroscopic surveys (RAVE, SDSS) are also a valuable source for the binary star research community. Identification of double-lined spectra is easy and it is not li
mited by the rare occurrences of eclipses. When the spectrum is properly classified, its atmospheric parameters can be calculated by comparing the spectrum with the best fit atmosphere model. We present the analysis of the binary stars from the sample of roughly 250.000 RAVE survey spectra. The classification and binary discovery method is based on the correlation function analysis. The comparison of these spectra with the model shows that it is possible to estimate the essential atmospheric parameters relatively well. Large number of such estimates and the fact that RAVE consists of a magnitude selected sample without any color cuts makes it suitable for a binary star population study.
