34 citations · 73 across the 12 of their papers we have counts for
12 papers
KIC 6464285: A Solar-type Eclipsing Binary in a Hierarchical Triple System with Quasi-periodic Out-of-eclipse Modulations
Fang-Bin Meng, Li-Ying Zhu, Sheng-Bang Qian +10
We present the first detailed analysis of the solar-type triple system KIC 6464285. Combining long-term, high-precision photometry from Kepler, TESS, and ZTF with low-resolution sp…
The Stellar Abundances and Galactic Evolution Survey (SAGES). V. The First Data Release of the DDO51 Band
Qiqian Zhang, Zhou Fan, Gang Zhao +20
We present the first public data release of DDO51 band from the Stellar Abundances and Galactic Evolution Survey (SAGES), based on Nanshan One-meter Wide-field Telescope (NOWT) obs…
Estimating stellar atmospheric parameters and elemental abundances using fully connected residual network
Shuo Li, Yin-Bi Li, A-Li Luo +3
Stellar atmospheric parameters and elemental abundances are traditionally determined using template matching techniques based on high-resolution spectra. However, these methods are…
Planets Across Space and Time (PAST). VIII : Kinematic Characterization and Identification of Radial Velocity Variables for the LAMOST-Gaia-TESS Stars
Di Wu, Di-Chang Chen, Ji-Wei Xie +6
The Transiting Exoplanet Survey Satellite (TESS) has discovered over 6700 nearby exoplanets candidates using the transit method through its all-sky survey. Characterizing the kinem…
Estimating Stellar Atmospheric Parameters and [α/Fe] for LAMOST O-M type Stars Using a Spectral Emulator
Jun-chao Liang, A-Li Luo, Yin-Bi Li +7
In this paper, we developed a spectral emulator based on the Mapping Nearby Galaxies at Apache Point Observatory Stellar Library (MaStar) and a grouping optimization strategy to es…
Measuring the Diffuse Interstellar Bands at 5780, 5797, and 6614 Å in Low-Resolution Spectra of Cool Stars from LAMOST
Xiao-Xiao Ma, Jian-Jun Chen, A-Li Luo +7
We attempt to measure the DIBs 5780, 5797 and 6614 in over two million low-resolution spectra of cool stars from LAMOST. Based on the DIB measurements, the correlation bet…
Deep learning interpretability analysis for carbon star identification in Gaia DR3
Shuo Ye, Wen-Yuan Cui, Yin-Bi Li +2
Context. A large fraction of Asymptotic Giant Branch (AGB) stars develop carbon-rich atmospheres during their evolution. Based on their color and luminosity, these carbon stars can…
Planets Across Space and Time (PAST). V. The evolution of hot Jupiters revealed by the age distribution of their host stars
Di-Chang Chen, Ji-Wei Xie, Ji-Lin Zhou +11
The unexpected discovery of hot Jupiters challenged the classical theory of planet formation inspired by our solar system. Until now, the origin and evolution of hot Jupiters are s…
Planets Across Space and Time (PAST) IV: The Occurrence and Architecture of Kepler Planetary Systems as a Function of Kinematic Age Revealed by the LAMOST-Gaia-Kepler Sample
Jia-Yi Yang, Di-Chang Chen, Ji-Wei Xie +7
One of the fundamental questions in astronomy is how planetary systems form and evolve. Measuring the planetary occurrence and architecture as a function of time directly addresses…
An update of the catalog of radial velocity standard stars from the APOGEE DR17
Qing-Zheng Li, Yang Huang, Xiao-Bo Dong
We present an updated catalog of 46,753 radial velocity (RV) standard stars selected from the APOGEE DR17. These stars cover the Northern and Southern Hemispheres almost evenly, wi…
Study on Outliers in the Big Stellar Spectral Dataset of the Fifth Data Release (DR5) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST)
Yan Lu, A-Li Luo, Li-Li Wang +10
To study the quality of stellar spectra of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and the correctness of the corresponding stellar parameters derive…
Analysis of Stellar Spectra from LAMOST DR5 with Generative Spectrum Networks
Wang Rui, Luo A-li, Zhang Shuo +9
In this study, the fundamental stellar atmospheric parameters (Teff, log g, [Fe/H] and [α/Fe]) were derived for low-resolution spectroscopy from LAMOST DR5 with Generative Spectrum…