相关论文: Stellar parameters from very low resolution spectr…

In this third paper in a series, we investigate the need of spectra denoising for the derivation of stellar parameters. We have used two distinct datasets for this work. The first one contains spectra in the range of 4450-5400 {\AA} at a…

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…

The GAIA Galactic survey satellite will obtain photometry in 15 filters of over 10^9 stars in our Galaxy across a very wide range of stellar types. No other planned survey will provide so much photometric information on so many stars. I…

A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we…

Stellar parameters for large samples of stars play a crucial role in constraining the nature of stars and stellar populations in the Galaxy. An increasing number of medium-band photometric surveys are presently used in estimating stellar…

New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic…

In this study, the fundamental stellar atmospheric parameters (Teff, log g, [Fe/H] and [{\alpha}/Fe]) were derived for low-resolution spectroscopy from LAMOST DR5 with Generative Spectrum Networks (GSN). This follows the same scheme as a…

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…

We present techniques for the estimation of stellar atmospheric parameters (Teff,logg,[Fe/H]) for stars from the SDSS/SEGUE survey. The atmospheric parameters are derived from the observed medium-resolution (R=2000) stellar spectra using…

In this follow-up paper, we investigate the use of Convolutional Neural Network for deriving stellar parameters from observed spectra. Using hyperparameters determined previously, we have constructed a Neural Network architecture suitable…

The growth of sky surveys and the large amount of stellar spectra in the current databases, has generated the necessity of developing new methods to estimate atmospheric parameters, a fundamental task on stellar research. In this work we…

Context. As increasingly more spectroscopic data are being delivered by medium- and high-resolving power multi-object spectrographs, more automatic stellar parameter determination softwares are being developed. The quality of the spectra…

Machine Learning is an efficient method for analyzing and interpreting the increasing amount of astronomical data that is available. In this study, we show, a pedagogical approach that should benefit anyone willing to experiment with Deep…

Gaia will obtain astrometry and spectrophotometry for essentially all sources in the sky down to a broad band magnitude limit of G=20, an expected yield of 10^9 stars. Its main scientific objective is to reveal the formation and evolution…

Studies of Galactic chemical and dynamical evolution in the solar neighborhood depend on the availability of precise atmospheric parameters (Teff, [Fe/H] and log g) for solar-type stars. Many large-scale spectroscopic surveys operate at low…

The search for twins of the Sun and Earth relies on accurate characterization of stellar and exoplanetary parameters: i.e., ages, masses, and radii. In the modern era of asteroseismology, parameters of solar-like stars are derived by…

We present a technique which employs artificial neural networks to produce physical parameters for stellar spectra. A neural network is trained on a set of synthetic optical stellar spectra to give physical parameters (e.g. T_eff, log g,…

Large spectroscopic surveys of the Milky Way need to be calibrated against a sample of benchmark stars to ensure the reliable determination of atmospheric parameters. We present new fundamental stellar parameters of seven giant and subgiant…

We present a method estimating the atmospheric parameters Teff, log g, [Fe/H] for stars observed, even at low signal to noise ratio, with the echelle spectrograph ELODIE on the 193cm telescope at Observatoire de Haute-Provence. The method…

Deriving stellar atmospheric parameters and chemical abundances from stellar spectra is crucial for understanding the evolution of the Milky Way. By performing a fitting with MARCS model atmospheric theoretical synthetic spectra combined…