activity
20242026
collaborators

9 papers

astro-ph.HE2026

Discovery of a Featureless Tidal Disruption Event at z~1 with the Wide Field Survey Telescope

Jiazheng Zhu, Zelin Xu, Ning Jiang +31

We report the discovery of tidal disruption event (TDE) WFST250820mmsw/AT2025wet by the 2.5-meter Wide Field Survey Telescope (WFST). It exhibits a blue nuclear flare throughout th…

astro-ph.GA2026

The FAST Hundred-Deg HI Deep (HD) Survey: Early Results from the Pilot Survey

Chen Xu, Yingjie Jing, Jie Wang +26

The Hundred-deg HI Deep (HD) survey carried out with the Five-hundred-meter Aperture Spherical Telescope (FAST) is planned to map a contiguous region within the DESI DR1 fo…

astro-ph.GA2026

SDSS+JWST Census of Stellar and Nebular Dust Attenuation at -7: Mass Dependence and Redshift Evolution

Jie Song, Masami Ouchi, Tomokazu Kiyota +3

We present the demography of dust attenuation, including its mass dependence and redshift evolution, using spectroscopic samples of 34,182 SDSS galaxies at and 863 JWST/…

astro-ph.GA2026

Robustness Analysis of USmorph: II. Optimizing Feature Extraction, Dimensionality Reduction, and Clustering for Unsupervised Galaxy Morphology Classification

Guanwen Fang, Xiaolei Yin, Yirui Zheng +5

We conduct a systematic robustness analysis of the unsupervised machine learning module within the hybrid framework \texttt{USmorph}. This module automatically discovers morphologi…

astro-ph.GA2025

Robustness Analysis of USmorph: I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification

Shiwei Zhu, Guanwen Fang, Yao Dai +5

We conduct a systematic robustness analysis of the hybrid machine learning framework \texttt{USmorph}, which integrates unsupervised and supervised learning for galaxy morphologica…

astro-ph.GA2025

An updated efficient galaxy morphology classification model based on ConvNeXt encoding with UMAP dimensionality reduction

Guanwen Fang, Shiwei Zhu, Jun Xu +5

We present an enhanced unsupervised machine learning (UML) module within our previous \texttt{USmorph} classification framework featuring two components: (1) hierarchical feature e…