Related papers: Estimating Stellar Parameters from LAMOST Low-reso…
Since September 2018, LAMOST starts a new 5-year medium-resolution spectroscopic survey (MRS) using bright/gray nights. We present the scientific goals of LAMOST-MRS and propose a near optimistic strategy of the survey. A complete footprint…
We present a library of high-resolution (R $\equiv$ $\lambda$/$\Delta$$\lambda$ $\sim$ 45,000) and high signal-to-noise ratio (S/N $\geq$ 200) near-infrared spectra for stars of a wide range of spectral types and luminosity classes. The…
Asteroseismology is a powerful tool to precisely determine the evolutionary status and fundamental properties of stars. With the unprecedented precision and nearly continuous photometric data acquired by the NASA Kepler mission, parameters…
In the current era of stellar spectroscopic surveys, synthetic spectral libraries are the basis for the derivation of stellar parameters and chemical abundances. In this paper, we compare the stellar parameters determined using five popular…
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…
The instrumental profile (IP) of a telescope is of great significance for spectroscopic analyses, especially for wavelength calibration and stellar parameter measurements. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope…
We built an optimal basis of low resolution templates for galaxies over the wavelength range from 0.2 to 10 $\mu$m using a variant of the algorithm presented by Budavari et al. (2000). We derived them using eleven bands of photometry from…
Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their…
With the advent of new spectroscopic surveys from ground and space, observing up to hundreds of millions of galaxies, spectra classification will become overwhelming for standard analysis techniques. To prepare for this challenge, we…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine…
We present an unbiased spectroscopic study of the Galactic supernova remnant (SNR) Cygnus Loop using the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) DR5. LAMOST features both a large field of view and a large…
M dwarfs are the dominating type of stars in the solar neighbourhood. They serve as excellent tracers for the study of the distribution and properties of the nearby interstellar dust. In this work, we aim to obtain high accuracy reddening…
Future satellite missions are expected to perform all-sky surveys, thus providing the entire sky near-infrared spectral data and consequently opening a new window to investigate the evolution of galaxies. Specifically, the infrared spectral…
We have examined the spectroscopic properties of a sample of 19 optically bright, low luminosity Flat Radio Spectrum (LL FRS) sources. Our study focuses on the properties of their host galaxies, namely the nuclear stellar populations and…
By comparing near-infrared spectra with atmosphere models, we infer the effective temperature, surface gravity, projected rotational velocity, and radial velocity for 21 very-low-mass stars and brown dwarfs. The unique sample consists of…
Machine learning has been widely applied to clearly defined problems of astronomy and astrophysics. However, deep learning and its conceptual differences to classical machine learning have been largely overlooked in these fields. The broad…
We present Starduster, a supervised deep learning model that predicts the multi-wavelength SED from galaxy geometry parameters and star formation history by emulating dust radiative transfer simulations. The model is comprised of three…
As a major component of the LAMOST Galactic surveys, the LAMOST Spectroscopic Survey of the Galactic Anti-centre (LSS-GAC) aims to survey a significant volume of the Galactic thin/thick discs and halo for a contiguous sky area of over 3,400…
We present a database of 908 spectra of 709 stars obtained with the ELODIE spectrograph at Observatoire de Haute-Provence. 52 orders of the echelle spectra have been carefully fitted together to provide continuous, high-resolution spectra…