An Empirical Sample of Spectra of M-type Stars with Homogeneous Atmospheric-Parameter Labels

TL;DR

This paper presents an empirical, high-quality spectral sample of 5105 M-type stars with homogeneous atmospheric parameters, improving parameter estimation accuracy for large spectroscopic surveys like LAMOST.

Contribution

It introduces a new empirical spectral sample with reliable labels and a neural network validation method, enhancing the precision of atmospheric parameters for M-type stars.

Findings

Achieved standard deviations of 14 K in Teff, 0.06 dex in log g, and 0.05 dex in [M/H] in neural network predictions.

Produced a high S/N spectral grid used in the LAMOST M-star pipeline, improving parameter precision.

Enhanced the accuracy of M-star parameters in LAMOST DR11 compared to DR9.

Abstract

The discrepancies between theoretical and observed spectra, and the systematic differences between various spectroscopic parameter estimates, complicate the determination of atmospheric parameters of M-type stars. In this work, we present an empirical sample of 5105 M-type star spectra with homogeneous atmospheric parameter labels through stellar-label transfer and sample cleaning. We addressed systematic discrepancies in spectroscopic parameter estimates by adopting recent results for Gaia EDR3 stars as a reference standard. Then, we used a density-based spatial clustering of applications with noise to remove unreliable samples in each subgrid of parameters. To confirm the reliability of the stellar labels, a 5-layer neural network was utilized, randomly partitioning the samples into training and testing sets. The standard deviations between the predicted and actual values in the testing set are 14 K for Teff , 0.06 dex for log g, and 0.05 dex for [M/H], respectively. In addition, we conducted an internal cross-validation to enhance validation and obtained precisions of 11 K, 0.05 dex, and 0.05 dex for Teff , log g, and [M/H], respectively. A grid of 1365 high Signal-to-Noise ratio (S/N) spectra and their labels, selected from the empirical sample, was utilized in the stellar parameter pipeline for M-Type stars (LASPM) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), producing an almost seamless Kiel distribution diagram for LAMOST DR10 and DR11 data. The atmospheric parameters for M-type stars from LAMOST DR11 show improved precision compared to the data from DR9, with improvements (for spectra with S/N higher than 10) from 118 to 67 K in Teff , 0.2 to 0.07 dex in log g, and 0.29 to 0.14 dex in [M/H].