4 citations · 4 across the 7 of their papers we have counts for
9 papers
LSTM-MDNz: Estimating Quasar Photometric Redshifts with an LSTM-Augmented Mixture Density Network
Jianzhen Chen, Zhijian Luo, Liping Fu +4
Quasar photometric redshifts are essential for studying cosmology and large-scale structures. However, their complex spectral energy distributions cause significant redshift-color…
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…
Detection of Quasi-periodic Oscillations in the -Ray Light Curve of 4FGL J0309.9-6058
Jingyu Wu, Zhihao Ouyang, Hubing Xiao +7
In this work, we report, for the first time, a quasi-periodic oscillation (QPO) in the -ray band of 4FGL J0309.9-6058, also known as PKS 0308-611. We employed three analytical m…
Identifying Dust-lane Spheroidal Galaxies in DESI Legacy Imaging Surveys Using Semi-Supervised Methods
Zhijian Luo, Jianzhen Chen, Wenxiang Pei +4
Dust-lane spheroidal galaxies (DLSGs) are unique astrophysical systems that exhibit the morphology of early-type galaxies (ETGs) but are distinguished by prominent dust lanes. Rece…
The averaged broadband spectral energy distribution study of Fermi bright BL Lac objects
Hubing Xiao, Haitao Cao, Rui Xue +6
The physics-determined broadband spectral energy distributions (SEDs) of blazars have been widely used to study the property during their flaring/outburst states, while the non-fla…
Galaxy Morphology Classification via Deep Semi-Supervised Learning with Limited Labeled Data
Zhijian Luo, Jianzhen Chen, Zhu Chen +4
Galaxy morphology classification plays a crucial role in understanding the structure and evolution of the universe. With galaxy observation data growing exponentially, machine lear…