Abstract Although high-resolution stellar spectra allow us to derive precise stellar labels (effective temperature, metallicity, surface gravity, elemental abundances, etc.) based on resolved atomic lines and molecular bands, low-resolution spectra have been proved to be competitive in determining many stellar labels at comparable precision. It is useful to consider the spectral information content when assessing the capability of a stellar spectrum in deriving precise stellar labels. In this work, we quantify the information content brought by the LAMOST-II medium-resolution spectroscopic survey (MRS) using the gradient spectra as well as the coefficients-of-dependence (CODs). In general, the wavelength coverage of the MRS well constrains the stellar labels but the sensitivities of different stellar labels vary with spectral types and metallicity of the stars of interest. Consequently, this affects the performance of the stellar label determination from the MRS spectra. By applying the SLAM method to the synthetic spectra which mimic the MRS data, we find that the precision of the fundamental stellar parameters Teff , log g and [M/H] are better when combining both the blue and red bands of the MRS. This is especially important for warm stars because the Hα line located in the red part plays a more important role in determining the effective temperature for warm stars. With blue and red parts together, we are able to reach similar performance to the low-resolution spectra except for warm stars. However, at [M/H] ∼ −2.0 dex, the uncertainties of fundamental stellar labels estimated from MRS are substantially larger than that from low-resolution spectra. We also tested the uncertainties of Teff , log g and [M/H] from MRS data induced from the radial velocity mismatch and find that a mismatch of about 1 km s−1, which is typical for LAMOST MRS data, would not significantly affect the stellar label estimates. Finally, reference precision limits are calculated using synthetic gradient spectra, according to which we expect abundances of at least 17 elements to be measured precisely from MRS spectra.
Keywords methods: data analysis — methods: statistical — stars: fundamental parameters — stars: abundances
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