activity
20192026
most citedRecognition of M-type stars in the unclassified spectra of LAMOST DR5 using a hash learning method

16 citations · 25 across the 10 of their papers we have counts for

collaborators

10 papers

astro-ph.IM2026

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference

Hai-Ling Lu, Yu-Yang Li, Yin-Bi Li +4

Stellar spectra encode key information on the physical properties and chemical compositions of stars. Accurate stellar parameter determination is essential for addressing major que…

astro-ph.IM2026

A Gaia-linked High-purity QSO Candidate Catalog in Selected Fields with Extinction-binned Calibration and Spectrum-informed Training

Zi-Huang Cao, Zhao-Xiang Qi, Juan-Juan Ren +11

We present an extinction-calibrated, Gaia-source-level QSO candidate catalog for selected fields, designed as a high-purity input catalog for fiber-spectroscopic follow-up rather t…

astro-ph.SR2026

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…

astro-ph.GA2026★ 1 cited

PhDLspec: physical-prior embedded deep learning method for spectroscopic determination of stellar labels in high-dimensional parameter space

Tianmin Wu, Maosheng Xiang, Jianrong Shi +4

Unlocking the full physical information encoded in low-resolution spectra poses a significant challenge for astronomical survey analysis. Such a task demands modeling spectra and o…

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.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…

astro-ph.GA2025

Measurements of the Diffuse Interstellar Bands at 5780, 5797, and 6614 Å in the Hot Stellar Spectra of the LAMOST LRS DR10

Xiao-Xiao Ma, A-Li Luo, Jian-Jun Chen +2

Diffuse Interstellar Bands (DIBs) are crucial tracers of the interstellar medium (ISM), yet their carriers remain poorly understood. While large-scale surveys have advanced DIB stu…

astro-ph.SR2025★ 4 cited

New Symbiotic Stars from LAMOST DR10 Spectra and Multi-band Photometry

Jing Chen, Liang Wang, Yin-Bi Li +5

Symbiotic star (SySt) is long-period interacting binary system, typically consisting of a white dwarf and a red giant surrounded by a nebula. These systems are natural astrophysica…

astro-ph.SR2022★ 3 cited

M Subdwarf Research III. Spectroscopic Diagnostics for Breaking Parameter Degeneracy

Shuo Zhang, Hua-Wei Zhang, Georges Comte +5

To understand the parameter degeneracy of M subdwarf spectra at low resolution, we assemble a large number of spectral features in the wavelength range of 0.6-2.5 μm with band stre…

astro-ph.IM2019★ 16 cited

Recognition of M-type stars in the unclassified spectra of LAMOST DR5 using a hash learning method

Y. -X. Guo, A. -L. Luo, S. Zhang +6

Our study aims to recognize M-type stars which are classified as "UNKNOWN" due to bad quality in Large sky Area Multi-Object fibre Spectroscopic Telescope (LAMOST) DR5 V1. A binary…