We present an automated procedure that derives simultaneously the effective
temperature Teffâ, the surface gravity logg, the metallicity [Fe/H], and
the equatorial projected rotational velocity vsini for "normal" A and Am stars.
The procedure is based on the principal component analysis inversion method of
Paletou et al. (2015a). A sample of 322 high resolution spectra of F0-B9 stars,
retrieved from the Polarbase, SOPHIE, and ELODIE databases, were used to test
this technique with real data. We have selected the spectral region from
4400-5000\AA\ as it contains many metallic lines and the Balmer HÎČ line.
Using 3 datasets at resolving powers of R=42000, 65000 and 76000, about
6.6x106 synthetic spectra were calculated to build a large learning
database. The Online Power Iteration algorithm was applied to these learning
datasets to estimate the principal components (PC). The projection of spectra
onto the few PCs offered an efficient comparison metric in a low dimensional
space. The spectra of the well known A0- and A1-type stars, Vega and Sirius A,
were used as control spectra in the three databases. Spectra of other well
known A-type stars were also employed in order to characterize the accuracy of
the inversion technique. All observational spectra were inverted and
atmospheric parameters derived. After removal of a few outliers, the
PCA-inversion method appears to be very efficient in determining Teffâ,
[Fe/H], and vsini for A/Am stars. The derived parameters agree very well with
previous determinations. Using a statistical approach, deviations of around 150
K, 0.35 dex, 0.15 dex, and 2 km/s were found for Teffâ, logg, [Fe/H], and
vsini with respect to literature values for A-type stars. The PCA-inversion
proves to be a very fast, practical, and reliable tool for estimating stellar
parameters of FGK and A stars, and deriving effective temperatures of M stars.Comment: 16 pages, 9 figures. Accepted in A&