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 astro-ph.GAShow all

14 papers · 1 filter

astro-ph.GA2026

Indirect evidence of the extinction bump within the dusty torus of SDSS J141945.50+524648.0

Ze Li, Gaoyang Chen, Qifan Cui +7

We present a multi-wavelength study of the quasar SDSS J141945.50524648.0 (), a member of the newly identified population of quasar-associated $2175\,\mathring{\mathrm…

astro-ph.GA2026

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…

astro-ph.GA2026

Tracing the kinematic perturbations of the Milky Way spiral arms with APOGEE DR17 and Gaia DR3

Xi-Can Tang, Zhi Li, Iulia T. Simion +4

Aims. We constrain the dynamical perturbations of the spiral arms in the Milky Way disk, based on the non-axisymmetric streaming motions of RGB stars revealed by APOGEE and \textit…

astro-ph.GA2026

Comparative analysis of missing data imputation methods for CSST survey: Impact on photometric redshift estimation performance

Ling Wang, Zhu Chen, Zhijian Luo +42

Improving the accuracy of photometric redshifts (photo-) is essential for reliable statistical studies of cosmology and galaxy evolution. However, missing photometric bands are…

astro-ph.GA2026

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…

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.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.GA2024

Photometric Redshift Estimation for CSST Survey with LSTM Neural Networks

Zhijian Luo, Yicheng Li, Junhao Lu +11

Accurate estimation of photometric redshifts (photo-s) is crucial for cosmological surveys. Various methods have been developed for this purpose, such as template fitting method…

astro-ph.GA2024★ 1 cited

A comparative study of ultraluminous infrared galaxies in the IRAS and SDSS Surveys

Shaohua Zhang, Zhijian Luo, Xiheng Shi +3

We present a comprehensive study of Ultraluminous Infrared Galaxies (ULIRGs), leveraging data from the IRAS Faint Source Catalogue (FSC) and the spectroscopic catalog in the Sloan…