StellarGAN: Classifying Stellar Spectra with Generative Adversarial Networks in SDSS and APOGEE Sky Surveys
Extracting precise stellar labels is crucial for large spectroscopic surveys like the Sloan Digital Sky Survey (SDSS) and APOGEE. In this paper, we report the newest implementation of StellarGAN, a data-driven method based on generative adversarial networks (GANs). Using 1D operators like convolutio...
Main Authors: | Wei Liu, Shuo Cao, Xian-Chuan Yu, Meng Zhu, Marek Biesiada, Jiawen Yao, Minghao Du |
---|---|
Format: | Article |
Language: | English |
Published: |
IOP Publishing
2024-01-01
|
Series: | The Astrophysical Journal Supplement Series |
Subjects: | |
Online Access: | https://doi.org/10.3847/1538-4365/ad29ef |
Similar Items
-
In the Trenches of the Solar–Stellar Connection. VII. Wilson–Bappu 2022
by: Thomas Ayres
Published: (2023-01-01) -
Inferring Stellar Parameters from Iodine-imprinted Keck/HIRES Spectra with Machine Learning
by: Jude Gussman, et al.
Published: (2024-01-01) -
Generating Stellar Spectra Using Neural Networks
by: Marwan Gebran
Published: (2024-01-01) -
The Shapes of Stellar Spectra
by: Carlos Allende Prieto
Published: (2023-03-01) -
Correlating Intrinsic Stellar Parameters with Mg ii Self-reversal Depths
by: Anna Taylor, et al.
Published: (2024-01-01)