1.3k citations · 32.1k across the 423 of their papers we have counts for
11 papers · 2 filters
Milky Way Satellite Census. II. Galaxy--Halo Connection Constraints Including the Impact of the Large Magellanic Cloud
E. O. Nadler, R. H. Wechsler, K. Bechtol +63
The population of Milky Way (MW) satellites contains the faintest known galaxies and thus provides essential insight into galaxy formation and dark matter microphysics. Here we com…
Milky Way Satellite Census. I. The Observational Selection Function for Milky Way Satellites in DES Y3 and Pan-STARRS DR1
A. Drlica-Wagner, K. Bechtol, S. Mau +55
We report the results of a systematic search for ultra-faint Milky Way satellite galaxies using data from the Dark Energy Survey (DES) and Pan-STARRS1 (PS1). Together, DES and PS1…
Birds of a Feather? Magellan/IMACS Spectroscopy of the Ultra-Faint Satellites Grus II, Tucana IV, and Tucana V
J. D. Simon, T. S. Li, D. Erkal +54
We present Magellan/IMACS spectroscopy of three recently discovered ultra-faint Milky Way satellites, Grus II, Tucana IV, and Tucana V. We measure systemic velocities of V_hel = -1…
Optimising Automatic Morphological Classification of Galaxies with Machine Learning and Deep Learning using Dark Energy Survey Imaging
Ting-Yun Cheng, Christopher J. Conselice, Alfonso Aragón-Salamanca +13
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear compar…
Constraining Radio Mode Feedback in Galaxy Clusters with the Cluster Radio AGN Properties to z1
N. Gupta, M. Pannella, J. J. Mohr +58
We study the properties of the Sydney University Molonglo Sky Survey (SUMSS) 843~MHz radio AGN population in galaxy clusters from two large catalogs created using the Dark Energy S…
An extended catalog of galaxy-galaxy strong gravitational lenses discovered in DES using convolutional neural networks
C. Jacobs, T. Collett, K. Glazebrook +55
We search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets…