activity
20232026
most citedThe Study of Jet Formation Mechanism in Fermi Blazars

4 citations · 6 across the 22 of their papers we have counts for

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Showing 2025Show all

9 papers · 1 filter

astro-ph.GA2025

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…

astro-ph.GA2025

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…

astro-ph.GA2025

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…

astro-ph.HE2025

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…

astro-ph.GA2025

Detecting Galactic Rings in the DESI Legacy Imaging Surveys with Semi-Supervised Deep Learning

Jianzhen Chen, Zhijian Luo, Cheng Cheng +3

The ring structures of disk galaxies are vital for understanding galaxy evolution and dynamics. However, due to the scarcity of ringed galaxies and challenges in their identificati…

astro-ph.GA2025

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…

astro-ph.GA2025

The Quasar-associated 2175 Å Dust Absorbers in the SDSS DR16 Quasar Catalog

Shaohua Zhang, Yuchong Luo, Shangchun Xie +4

We present, for the first time, a systematic study of quasar-associated 2175 Å dust absorbers using spectroscopic data from the Sloan Digital Sky Survey (SDSS) Data Release 16 (DR1…

astro-ph.GA2025

A random walk model for the evolution of the halo spin vector

Jun Hou, Zhijian Luo, Cedric G. Lacey

We follow the spin vector evolutions of well resolved dark matter haloes (containing more than 300 particles) in merger tree main branches from the Millennium and Millennium-II N-b…

astro-ph.CO2025

Improving Photometric Redshift Estimation for CSST Mock Catalog Using SED Templates Calibrated with Perturbation Algorithm

Yicheng Li, Liping Fu, Zhu Chen +11

Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of its high efficiency. Although various methods have been develo…