5.4k citations · 27.8k across the 235 of their papers we have counts for
238 papers
Dark Energy Survey Year 3 results: Simulation-based CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design
A. Thomsen, J. Bucko, T. Kacprzak +99
Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. This work presents the f…
Dark Energy Survey Year 6 Results: Photometric Data Set for Cosmology
K. Bechtol, I. Sevilla-Noarbe, A. Drlica-Wagner +103
We describe the photometric data set assembled from the full six years of observations by the Dark Energy Survey (DES) in support of static-sky cosmology analyses. DES Y6 Gold is a…
SPT Clusters with DES and HST Weak Lensing. I. Cluster Lensing and Bayesian Population Modeling of Multi-Wavelength Cluster Datasets
S. Bocquet, S. Grandis, L. E. Bleem +130
We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using…
Dark Energy Survey Year 6 Results: Intra-Cluster Light from Redshift 0.2 to 0.5
Yuanyuan Zhang, Jesse B. Golden-Marx, Ricardo L. C. Ogando +46
Using the full six years of imaging data from the Dark Energy Survey, we study the surface brightness profiles of galaxy cluster central galaxies and intra-cluster light. We apply…
DeepZipper II: Searching for Lensed Supernovae in Dark Energy Survey Data with Deep Learning
Robert Morgan, B. Nord, K. Bechtol +64
Gravitationally lensed supernovae (LSNe) are important probes of cosmic expansion, but they remain rare and difficult to find. Current cosmic surveys likely contain and 5-10 LSNe i…
DeepZipper: A Novel Deep Learning Architecture for Lensed Supernovae Identification
Robert Morgan, B. Nord, K. Bechtol +48
Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectro…