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20242026
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7 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

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…