6 papers
MSFA-Net: An Advanced Deep Learning Model for Identifying Blue Horizontal-Branch Stars from LAMOST DR12
Mingyuan Wang, Xiaoming Kong, Jie Ju +2
Blue horizontal-branch (BHB) stars are low-mass, core helium-burning objects with nearly constant luminosities, making them powerful tracers of old, metal-poor populations and valu…
A Generalist Model Including Evolved Star Mass and Age
Mengmeng Zhang, Yude Bu, Siqi Wang +10
Determining precise stellar ages and masses for evolved giants is crucial for Galactic archaeology but challenged by spectral degeneracies. Gaia's low-resolution XP spectra offer a…
PhysFormer: A Physics-Embedded Generative Model for Physically Self-Consistent Spectral Synthesis
Siqi Wang, Mengmeng Zhang, Yude Bu +1
In scientific and engineering domains, modeling high-dimensional complex systems governed by partial differential equations (PDEs) remains challenging in terms of physical consiste…
Deep learning-driven atmospheric parameter prediction for hot subdwarf stars with synthetic and observed spectra
Zhenxin Lei, Yangyang Dong, Bokai Kou +4
We design a convolutional neural network (CNN) incorporating channel attention and spatial attention mechanisms to predict atmospheric parameters of hot subdwarfs. The experimental…
Identifying Ring Galaxies in DESI Legacy Imaging Surveys Using Machine Learning Methods
Aina Zhang, Xiaoming Kong, Bowen Liu +4
The formation and evolution of ring structures in galaxies are crucial for understanding the nature and distribution of dark matter, galactic interactions, and the internal secular…
Deblending Overlapping Galaxies in DECaLS Using Transformer-Based Algorithm: A Method Combining Multiple Bands and Data Types
Ran Zhang, Meng Liu, Zhenping Yi +8
In large-scale galaxy surveys, particularly deep ground-based photometric studies, galaxy blending is inevitable and poses a potential primary systematic uncertainty for upcoming s…