Stellar pulsation offers a unique opportunity to constrain the intrinsic parameters of stars and to unveil their inner structure. Kepler satellite is collecting a huge amount of data of unprecedent photometric precision, that will allow us to test theory and obtain a very precise tomography of stellar interiors. Aiming at providing the stars' fundamental parameters (Teff, logg, vsini, and luminosity) which are needed for computing asteroseismic models and interpreting Kepler data, we report spectroscopic observations of 23 early-type Kepler asteroseismic targets and 13 other stars in the Kepler field, but not selected to be observed. The cross-correlation with template spectra was used for measuring the radial velocity with the aim of identifying non-single stars. Spectral synthesis has been performed in order to derive the stellar parameters for our target stars. State-of-art LTE atmospheric models have been computed. For all the stars of our sample, we derive the radial velocity, Teff, logg, vsini, and luminosities. Further, for 12 stars, we perform a detailed abundance analysis of 20 species; for 16, we could derive only the [Fe/H] ratio. A spectral classification has been also performed for 17 stars in the sample. We found two double-lined spectroscopic binaries, HIP96299 and HIP98551, the former of which is an already known eclipsing binary, and two single-lined spectroscopic binaries, HIP97254 and HIP97724. We also report two suspected spectroscopic binaries, HIP92637 and HIP96762, and the detection of a possible variability of the radial velocity of HIP96277. Two of our program stars turn out to be chemically peculiar, namely HIP93941, which we classify as B2 He-weak, and HIP96210, which we classify as B6Mn. Finally, we find that HIP93522, HIP93941, HIP93943, HIP96210 and HIP96762, are very slow rotators (vsini<20km/s) which makes them very interesting and promising targets for an asteroseismic modeling.
Cone search capability for table J/A+A/517/A3/table3 (Stellar parameters derived for our stars)
Associated data
