296 citations · 1.6k across the 26 of their papers we have counts for
6 papers · 1 filter
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…
Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks
Ting-Yun Cheng, Christopher J. Conselice, Alfonso Aragón-Salamanca +57
We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3…
Pushing automated morphological classifications to their limits with the Dark Energy Survey
J. Vega-Ferrero, H. Domínguez Sánchez, M. Bernardi +60
We present morphological classifications of 27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classif…
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…
Is diffuse intracluster light a good tracer of the galaxy cluster matter distribution?
H. Sampaio-Santos, Y. Zhang, R. L. C. Ogando +64
We explore the relation between diffuse intracluster light (central galaxy included) and the galaxy cluster (baryonic and dark) matter distribution using a sample of 528 clusters a…
Dark matter halo properties of GAMA galaxy groups from 100 square degrees of KiDS weak lensing data
M. Viola, M. Cacciato, M. Brouwer +24
The Kilo-Degree Survey (KiDS) is an optical wide-field survey designed to map the matter distribution in the Universe using weak gravitational lensing. In this paper, we use these…