The power of low-resolution spectroscopy: On the spectral classification of planet candidates in the ground-based CoRoT follow-up

Planetary transits detected by the CoRoT mission can be mimicked by a low-mass star in orbit around a giant star. Spectral classification helps to identify the giant stars and also early-type stars which are often excluded from further follow-up. We study the potential and the limitations of low-resolution spectroscopy to improve the photometric spectral types of CoRoT candidates. In particular, we want to study the influence of the signal-to-noise ratio (SNR) of the target spectrum in a quantitative way. We built an own template library and investigate whether a template library from the literature is able to reproduce the classifications. Including previous photometric estimates, we show how the additional spectroscopic information improves the constraints on spectral type. Low-resolution spectroscopy ($R\approx$1000) of 42 CoRoT targets covering a wide range in SNR (1-437) and of 149 templates was obtained in 2012-2013 with the Nasmyth spectrograph at the Tautenburg 2m telescope. Spectral types have been derived automatically by comparing with the observed template spectra. The classification has been repeated with the external CFLIB library. The spectral class obtained with the external library agrees within a few sub-classes when the target spectrum has a SNR of about 100 at least. While the photometric spectral type can deviate by an entire spectral class, the photometric luminosity classification is as close as a spectroscopic classification with the external library. A low SNR of the target spectrum limits the attainable accuracy of classification more strongly than the use of external templates or photometry. Furthermore we found that low-resolution reconnaissance spectroscopy ensures that good planet candidates are kept that would otherwise be discarded based on photometric spectral type alone.
Comment: accepted for publication in Astronomische Nachrichten; 12 pages, 4 figures, 7 tables