5 papers
Enhancing Photometric Redshift Estimation for LSST with a Hybrid LSTM-Mixture Density Network
Zhijian Luo, Yangyang Li, Xinyu Luo +4
Accurate photometric redshift (photo-) estimation and robust uncertainty quantification are essential for the LSST to achieve its precision cosmology goals. Traditional machine…
Beyond Colors: Probing Redshifts from Galaxy Morphology in Single-band Images with ViT-MDNz
Zhijian Luo, Yangyang Li, Jianzhen Chen +5
To address the challenge of estimating redshifts when only single-band images are available, this study introduces a deep learning model named ViT-MDNz. Leveraging robust statistic…
BALNet: Deep Learning-Based Detection and Measurement of Broad Absorption Lines in Quasar Spectra
Yangyang Li, Zhijian Luo, Shaohua Zhang +5
Broad absorption line (BAL) quasars serve as critical probes for understanding active galactic nucleus (AGN) outflows, black hole accretion, and cosmic evolution. To address the li…
Investigating non-LTE abundances of Neodymium (Nd) in metal-poor FGK stars
John D. Dixon, Rana Ezzeddine, Yangyang Li +3
The dominant site(s) of the -process are a subject of current debate. Ejecta from -process enrichment events like kilonovae are difficult to directly measure, so we must inst…
NLTE abundances of Eu for a sample of metal-poor stars in the Galactic Halo and Metal-poor Disk with 1D and <3D> models
Yanjun Guo, Nicholas Storm, Maria Bergemann +6
Accurate measurements of europium abundances in cool stars are essential for an enhanced understanding of the r-process mechanisms. We measure the abundance of Eu in solar spectra…