77 citations · 174 across the 25 of their papers we have counts for
7 papers · 1 filter
Identifying AGN host galaxies with convolutional neural networks
Ziting Guo, John F. Wu, Chelsea E. Sharon
Active galactic nuclei (AGN) are supermassive black holes with luminous accretion disks found in some galaxies, and are thought to play an important role in galaxy evolution. Howev…
Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program
Elise Darragh-Ford, John F. Wu, Yao-Yuan Mao +39
We introduce the DESI LOW-Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift ta…
Identification of Galaxy-Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning
E. A. Zaborowski, A. Drlica-Wagner, F. Ashmead +88
We perform a search for galaxy-galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local V…
A Machine Learning Approach to Enhancing eROSITA Observations
John Soltis, Michelle Ntampaka, John Wu +5
The eROSITA X-ray telescope, launched in 2019, is predicted to observe roughly 100,000 galaxy clusters. Follow-up observations of these clusters from Chandra, for example, will be…
LADUMA: Discovery of a luminous OH megamaser at
Marcin Glowacki, Jordan D. Collier, Amir Kazemi-Moridani +65
In the local Universe, OH megamasers (OHMs) are detected almost exclusively in infrared-luminous galaxies, with a prevalence that increases with IR luminosity, suggesting that they…
The DECam Local Volume Exploration Survey Data Release 2
A. Drlica-Wagner, P. S. Ferguson, M. Adamów +121
We present the second public data release (DR2) from the DECam Local Volume Exploration survey (DELVE). DELVE DR2 combines new DECam observations with archival DECam data from the…