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astro-ph.GA2025★ 1 cited
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…
astro-ph.IM2025
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…
astro-ph.SR2025
Refined M-type Star Catalog from LAMOST DR10: Measurements of Radial Velocities, , log , [M/H] and [/M]
Shuo Li, Yin-Bi Li, A-Li Luo +10
Precise stellar parameters for M-type stars, the Galaxy's most common stellar type, are crucial for numerous studies. In this work, we refined the LAMOST DR10 M-type star catalog t…