1.2k citations · 9.1k across the 125 of their papers we have counts for
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Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data
G. Zacharegkas, C. Chang, J. Prat +100
We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing…
Weak Gravitational Lensing around Low Surface Brightness Galaxies in the DES Year 3 Data
N. Chicoine, J. Prat, G. Zacharegkas +102
We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diff…
The mass profiles of dwarf galaxies from Dark Energy Survey lensing
Joseph Thornton, Alexandra Amon, Risa H. Wechsler +7
We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterise their stellar mass and…
Cosmological shocks around galaxy clusters: A coherent investigation with DES, SPT & ACT
D. Anbajagane, C. Chang, E. J. Baxter +111
We search for signatures of cosmological shocks in gas pressure profiles of galaxy clusters using the cluster catalogs from three surveys: the Dark Energy Survey (DES) Year 3, the…
The Evolution of AGN Activity in Brightest Cluster Galaxies
T. Somboonpanyakul, M. McDonald, A. Noble +73
We present the results of an analysis of Wide-field Infrared Survey Explorer (WISE) observations on the full 2500 deg^2 South Pole Telescope (SPT)-SZ cluster sample. We describe a…
Dwarf AGNs from Optical Variability for the Origins of Seeds (DAVOS): Insights from the Dark Energy Survey Deep Fields
Colin J. Burke, Xin Liu, Yue Shen +69
We present a sample of 706, active galactic nuclei (AGNs) selected from optical photometric variability in three of the Dark Energy Survey (DES) deep fields (E2, C3, and…
A machine learning approach to galaxy properties: joint redshift-stellar mass probability distributions with Random Forest
S. Mucesh, W. G. Hartley, A. Palmese +72
We demonstrate that highly accurate joint redshift-stellar mass probability distribution functions (PDFs) can be obtained using the Random Forest (RF) machine learning (ML) algorit…
Probing galaxy evolution in massive clusters using ACT and DES: splashback as a cosmic clock
Susmita Adhikari, Tae-hyeon Shin, Bhuvnesh Jain +113
We measure the projected number density profiles of galaxies and the splashback feature in clusters selected by the Sunyaev--Zeldovich (SZ) effect from the Advanced Atacama Cosmolo…