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We utilized the Stellar LAbel Machine (SLAM), a data-driven model based on Support Vector Regression, to derive stellar parameters ([Fe/H], $T_{\rm eff}$, and $\log{g}$) for SDSS-V M dwarfs using low-resolution optical spectra (R$\sim$2000)…

To understand the parameter degeneracy of M subdwarf spectra at low resolution, we assemble a large number of spectral features in the wavelength range of 0.6-2.5 {\mu}m with band strength quantified by narrowband indices. Based on the…

Solar and Stellar Astrophysics · Physics 2023-01-18 Shuo Zhang , Hua-Wei Zhang , Georges Comte , Derek Homeier , Rui Wang , Neda Hejazi , Yin-Bi Li , A-Li Luo

The determination of atmospheric parameters is the first and most fundamental step in the analysis of a stellar spectrum. Current and forthcoming surveys involve samples of up to several million stars, and therefore fully automated…

Astrophysics · Physics 2009-11-13 C. Allende Prieto

M dwarf stars are the most common stars in the Galaxy, dominating the population of the Galaxy by numbers at faint magnitudes. Precise and accurate stellar parameters for M dwarfs are of crucial importance for many studies. However, the…

Solar and Stellar Astrophysics · Physics 2021-04-21 Jiadong Li , Chao Liu , Bo Zhang , Hao Tian , Dan Qiu , Haijun Tian

Atmospheric properties of F-,G- and K-type stars can be measured by spectral model fitting. These methods require data with good signal-to-noise ratio and reliable continuum normalisation. This is particularly challenging for the spectra we…

Solar and Stellar Astrophysics · Physics 2018-05-09 Samuel Gill , Pierre. F. L. Maxted , Barry Smalley

Large scale, deep survey missions such as GAIA will collect enormous amounts of data on a significant fraction of the stellar content of our Galaxy. These missions will require a careful optimisation of their observational systems in order…

Astrophysics · Physics 2010-10-28 Coryn A. L. Bailer-Jones

Understanding the atmospheric parameters of stars on the top of the RGB is essential to reveal the chemical composition of the Milky Way, as they can be used to probe the farthest parts of our Galaxy. Our goal is to determine the chemical…

Solar and Stellar Astrophysics · Physics 2024-04-23 Z. Dencs , A. Derekas , T. Mitnyan , M. F. Andersen , B. Cseh , F. Grundahl , V. Hegedűs , J. Kovács , L. Kriskovics , P. L. Palle , A. Pál , L. Szigeti , Sz. Mészáros

With the purpose of assessing classic spectroscopic methods on high-resolution and high signal-to-noise ratio spectra in the near-infrared wavelength region, we selected a sample of 65 F-, G-, and K-type stars observed with CARMENES, the…

We present a value-added catalog containing stellar parameters estimated from 7.10 million low-resolution spectra for 5.16 million unique stars with spectral signal-to-noise ratios (SNRs) higher than 10 obtained by the Large Sky Area…

Solar and Stellar Astrophysics · Physics 2022-04-06 Chun Wang , Yang Huang , Haibo Yuan , Huawei Zhang , Maosheng Xiang , Xiaowei Liu

A main science goal for the Large Synoptic Survey Telescope (LSST) is to measure the cosmic shear signal from weak lensing to extreme accuracy. One difficulty, however, is that with the short exposure time ($\simeq$15 seconds) proposed, the…

For high-contrast imaging (HCI) systems, such as VLT/SPHERE, the performance of the system at small angular separations is contaminated by the wind-driven halo in the science image. This halo is a result of the servo-lag error in the…

Instrumentation and Methods for Astrophysics · Physics 2020-04-22 M. A. M. van Kooten , Niek Doelman , Matthew Kenworthy

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…

Solar and Stellar Astrophysics · Physics 2024-10-23 Bing Du , A-Li Luo , Song Wang , Yinbi Li , Cai-Xia Qu , Xiao Kong , Yan-xin Guo , Yi-han Song , Fang Zuo

This work investigates the spectrum parameterization problem using deep neural networks (DNNs). The proposed scheme consists of the following procedures: first, the configuration of a DNN is initialized using a series of autoencoder neural…

Solar and Stellar Astrophysics · Physics 2019-03-20 Xiangru Li , Ruyang Pan

We explore the application of artificial neural networks (ANNs) for the estimation of atmospheric parameters (Teff, logg, and [Fe/H]) for Galactic F- and G-type stars. The ANNs are fed with medium-resolution (~ 1-2 A) non flux-calibrated…

Employing a new machine learning method, named hierarchical extreme learning machine (HELM) algorithm, we identified 56 hot subdwarf stars in the first data release (DR1) of the Large Sky Area Multi-Object Fibre Spectroscopic Telescope…

Solar and Stellar Astrophysics · Physics 2019-07-02 Zhenxin Lei , Yude Bu , Jingkun Zhao , Péter Németh , Gang Zhao

Modern large-scale photometric surveys have provided us with multi-band photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (\teff) and metallicities (\feh), absolute…

Solar and Stellar Astrophysics · Physics 2023-07-11 Mingxu Sun , Bingqiu Chen , Helong Guo , He Zhao , Ming Yang , Wenyuan Cui

Deriving atmospheric parameters of a large sample of stars is of vital importance to understand the formation and evolution of the Milky Way. Photometric surveys, especially those with near-ultraviolet filters, can offer accurate…

Solar and Stellar Astrophysics · Physics 2024-01-15 Ruifeng Shi , Yang Huang , Xinyi Li , Huawei Zhang

We present a method to estimate distances to stars with spectroscopically derived stellar parameters. The technique is a Bayesian approach with likelihood estimated via comparison of measured parameters to a grid of stellar isochrones, and…

A library of 211 echelle spectra taken with ELODIE at the Observatoire de Haute-Provence is presented. It provides a set of spectroscopic standards covering the full range of gravities and metallicities in the effective temperature interval…

Astrophysics · Physics 2009-10-30 C. Soubiran , D. Katz , R. Cayrel