66 citations · 134 across the 5 of their papers we have counts for
5 papers
PISP: Projected-Space Inference of Stellar Parameters
Jun-Chao Liang, Yin-Bi Li, A-Li Luo +12
To improve the accuracy and efficiency of high-dimensional stellar parameter inference in large spectroscopic datasets, we propose a projection-assisted parameter-inference framewo…
Scalable Stellar Parameter Inference Using Python-based LASP: From CPU Optimization to GPU Acceleration
Jun-Chao Liang, Yin-Bi Li, A-Li Luo +13
To enhance the efficiency, scalability, and cross-survey applicability of stellar parameter inference in large spectroscopic datasets, we present a modular, parallelized Python fra…
Radial velocity measurements from LAMOST medium-resolution spectroscopic observations: A pointing towards the Kepler field
Nian Liu, Jian-Ning Fu, Weikai Zong +20
Radial velocity is one of key measurements in understanding the fundamental properties of stars, stellar clusters and the Galaxy. A plate of stars in the Kepler field were observed…
Carbon stars identified from LAMOST DR4 using Machine Learning
Yin-Bi Li, A-Li Luo, Chang-De Du +27
In this work, we present a catalog of 2651 carbon stars from the fourth Data Release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST). Using an effici…
LAMOST Spectrograph Response Curves: Stability and Application to flux calibration
Bing Du, A-Li Luo, Zhong-Rui Bai +14
The task of flux calibration for LAMOST (Large sky Area Multi-Object Spectroscopic Telescope) spectra is difficult due to many factors. For example, the lack of standard stars, fla…