Parameter Estimation of LAMOST Medium-resolution Stellar Spectra

Abstract

This paper investigates the problem of estimating three stellar atmospheric physical parameters and thirteen elemental abundances for medium-resolution spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Typical characteristics of these spectra are their huge scale, wide range of spectral signal-to-noise ratios, and uneven distribution in parameter space.These characteristics lead to unsatisfactory results on the spectra with low temperature, high temperature or low metallicity.To this end, this paper proposes a Stellar Parameter Estimation method based on Multiple Regions (SPEMR) that effectively improves parameter estimation accuracy. On the spectra with {S/N $\ge 10$}, the precisions are 47 K, 0.08 dex, 0.03 dex respectively for the estimations of ($T_{\mathrm{eff}}$, $\log g$ and $[Fe/H]$), 0.03 dex to 0.06 dex for elements C, Mg, Al, Si, Ca, Mn and Ni, 0.07 dex to 0.13 dex for N, O, S, K and Ti, while that of Cr is 0.16 dex.For the reference of astronomical science researchers and algorithm researchers, we released a catalog for 4.19 million medium-resolution spectra from the LAMOST DR8, experimental code, trained model, training data, and test data.

arXiv comment19 pages, 19 figures, 2 tables

References in corpus (25)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Array Programming with NumPy
• Binary companions of evolved stars in APOGEE DR14: Search method and catalog of ~5,000 companions
• MESA Isochrones and Stellar Tracks (MIST). I: Solar-Scaled Models
• MESA Isochrones and Stellar Tracks (MIST) 0: Methods for the construction of stellar isochrones
• The Apache Point Observatory Galactic Evolution Experiment (APOGEE)
• The First Data Release (DR1) of the LAMOST general survey
• The GALAH Survey: Scientific Motivation
• ASPCAP: The Apogee Stellar Parameter and Chemical Abundances Pipeline
• The GALAH+ Survey: Third Data Release
• A database of high and medium-resolution stellar spectra
• The Payne: self-consistent ab initio fitting of stellar spectra
• Automatic Determination of Stellar Atmospheric Parameters and Construction of Stellar Spectral Templates of the Guoshoujing Telescope (LAMOST)
• The chemical homogeneity of open clusters
• An Application of Deep Neural Networks in the Analysis of Stellar Spectra
• The K giant stars from the LAMOST survey data I: identification, metallicity, and distance
• Galactic Doppelganger: The chemical similarity among field stars and among stars with a common birth origin
• SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey
• The Gaia-ESO Survey: CNO abundances in the open clusters Trumpler 20, NGC 4815, and NGC 6705
• Exploring open cluster properties with Gaia and LAMOST
• Properties of Radial Velocities measurement based on LAMOST-II Medium-Resolution Spectroscopic Observations
• Assessing the performance of LTE and NLTE synthetic stellar spectra in a machine learning framework
• Analysis of Stellar Spectra from LAMOST DR5 with Generative Spectrum Networks
• Estimating Atmospheric Parameters from LAMOST Low-Resolution Spectra with Low SNR
• A Model RRNet for Spectral Information Exploitation and LAMOST Medium-resolution Spectrum Parameter Estimation