activity
20182026
most citedEfficient Selection of Quasar Candidates Based on Optical and Infrared Photometric Data Using Machine Learning

45 citations · 90 across the 12 of their papers we have counts for

collaborators
Showing astro-ph.GAShow all

6 papers · 1 filter

astro-ph.GA2026

Physical Properties of 6.7 Million Galaxies from the DESI Bright Galaxy Survey: Spectral Fitting and Systematic Tests with Mock Spectra

Niu Li, Hu Zou, Jinfu Gou +7

We present a comprehensive analysis of the physical properties of galaxies in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) Bright Galaxy Survey (BGS), based…

astro-ph.GA2026

Environmental Imprints on the Assembly of the Cool Gas around Bright Cluster Galaxies

Runyu Zhu, Hu Zou, Taotao Fang +14

Galaxy clusters represent extreme cosmic laboratories where environmental processes dramatically reshape their constituent galaxies, yet their effect on the gaseous halos of centra…

astro-ph.GA2026★ 1 cited

Discovery of low-redshift analogues to "Little Red Dots" in DESI: A later evolutionary stage of compact LRDs?

Weiyu Ding, Xu Kong, Wei-Jian Guo +8

The James Webb Space Telescope (JWST) has recently discovered a population of compact, red sources at z > 4 known as "Little Red Dots" (LRDs). They are characterized by their V-sha…

astro-ph.GA2025

Galaxy clusters from the DESI Legacy Imaging Surveys -- III. Star-forming fraction of brightest cluster galaxies

Shufei Liu, Hu Zou, Jinfu Gou +10

This study investigates the evolution of the star-forming fraction () of Brightest Cluster Galaxies (BCGs) at , using the galaxy clusters identified from th…

astro-ph.GA2024★ 1 cited

Search for young stellar objects within 4XMM-DR13 using CatBoost and SPE

Xiangyao Ma, Yanxia Zhang, Jingyi Zhang +3

Classifying and summarizing large data sets from different sky survey projects is essential for various subsequent scientific research. By combining data from 4XMM-DR13, SDSS DR18,…

astro-ph.GA2023★ 2 cited

Machine learning-based photometric classification of galaxies, quasars, emission-line galaxies, and stars

Fatemeh Zahra Zeraatgari, Fatemeh Hafezianzade, Yanxia Zhang +4

This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; star…