581 citations · 4.1k across the 72 of their papers we have counts for
Showing 2024 · astro-ph.GAShow all
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astro-ph.GA2024★ 4 cited
Photometric Selection of type 1 Quasars in the XMM-LSS Field with Machine Learning and the Disk-Corona Connection
Jian Huang, Bin Luo, W. N. Brandt +4
We present photometric selection of type 1 quasars in the XMM-Large Scale Structure (XMM-LSS) survey field with machine learning. We constructed our trai…
astro-ph.GA2024
Dust-Obscured Galaxies in the XMM-SERVS Fields: Selection, Multiwavelength Characterization, and Physical Nature
Zhibo Yu, W. N. Brandt, Fan Zou +7
Dust-obscured galaxies (DOGs) are enshrouded by dust, and many are believed to host accreting supermassive black holes (SMBHs), which makes them unique objects for probing the coev…
astro-ph.GA2024
The Cosmic Evolution of the Supermassive Black Hole Population: A Hybrid Observed Accretion and Simulated Mergers Approach
Fan Zou, W. N. Brandt, Elena Gallo +4
Supermassive black holes (SMBHs) can grow through both accretion and mergers. It is still unclear how SMBHs evolve under these two channels from high redshifts to the SMBH populati…