Exploring the spectral \textit{information content} in the LAMOST medium-resolution survey (MRS)
Bo Zhang, Chao Liu, Chun-Qian Li, Li-Cai Deng, Tai-Sheng Yan,, Jian-Rong Shi

TL;DR
This study quantifies the spectral information content of the LAMOST-II medium-resolution survey, revealing how spectral types, metallicity, and wavelength coverage influence the precision of stellar label determinations, and establishing expected measurement limits.
Contribution
It introduces a method to quantify spectral information content in medium-resolution spectra and assesses the impact of spectral coverage and stellar properties on label precision.
Findings
Blue and red spectral bands improve stellar parameter precision.
Hα line is crucial for warm star temperature determination.
Uncertainties increase at low metallicity ([M/H]~-2.0 dex).
Abstract
Low-resolution spectra are proved competitive to high-resolution spectra 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 and 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 and, therefore, affect the performance of the stellar label determination from the MRS spectra. Applying the SLAM to the synthetic spectra which mimic the MRS data, we find the precision of the fundamental stellar parameters Teff,…
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