5 citations · 5 across the 5 of their papers we have counts for
5 papers
DCNNAnaCal: Physics-Informed Machine Learning for Accurate and Precise Weak Lensing Shear Estimation
Shurui Lin, Xiangchong Li, Ji Li +3
Traditional weak gravitational lensing shear estimators are carefully calibrated but struggle to fully capture realistic galaxy morphologies, point-spread-function (PSF) effects, b…
Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-Selected AGNs in the Dark Energy Survey Deep Fields
Yichen Liu, Colin J. Burke, Diego Miura +4
We study the black hole mass host galaxy stellar mass relation, , for a sample of 706 and optically-variable active galac…
A Systematic Search for Candidate Supermassive Black Hole Binaries Using Periodic Mid-Infrared Light Curves of Active Galactic Nuclei
Di Luo, Ning Jiang, Xin Liu
Periodic variability in active galactic nuclei (AGNs) is a promising method for studying sub-parsec supermassive black hole binaries (SMBHBs), which are a challenging detection tar…
DAVOS: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds: Properties of Variability-Selected Active Galactic Nuclei in the COSMOS Field and Expectations for the Rubin Observatory
Colin J. Burke, Yichen Liu, Charlotte A. Ward +3
We study the black hole mass host galaxy stellar mass relation, , of a sample of optically-variable AGNs in the COSMOS field. The parent sample of 4…
Massive Black Hole Binaries as LISA Precursors in the Roman High Latitude Time Domain Survey
Zoltán Haiman, Chengcheng Xin, Tamara Bogdanović +27
With its capacity to observe faint active galactic nuclei (AGN) out to redshift , Roman is poised to reveal a population of b…