319 citations · 3.4k across the 66 of their papers we have counts for
36 papers · 1 filter
The Dark Energy Survey Supernova Program: Modelling selection efficiency and observed core collapse supernova contamination
M. Vincenzi, M. Sullivan, O. Graur +79
The analysis of current and future cosmological surveys of type Ia supernovae (SNe Ia) at high-redshift depends on the accurate photometric classification of the SN events detected…
Dark Energy Survey Year 3 Results: Calibration of Lens Sample Redshift Distributions using Clustering Redshifts with BOSS/eBOSS
R. Cawthon, J. Elvin-Poole, A. Porredon +83
We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform thi…
Dark Energy Survey Year 3 Results: Deep Field Optical + Near-Infrared Images and Catalogue
W. G. Hartley, A. Choi, A. Amon +115
We describe the Dark Energy Survey (DES) Deep Fields, a set of images and associated multi-wavelength catalogue () built from Dark Energy Camera (DECam) and Visible and…
Dark Energy Survey Year 3 Results: Covariance Modelling and its Impact on Parameter Estimation and Quality of Fit
O. Friedrich, F. Andrade-Oliveira, H. Camacho +109
We describe and test the fiducial covariance matrix model for the combined 2-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) dataset. Using a variety of new ansat…
DES Y3 results: Blending shear and redshift biases in image simulations
N. MacCrann, M. R. Becker, J. McCullough +93
As the statistical power of galaxy weak lensing reaches percent level precision, large, realistic and robust simulations are required to calibrate observational systematics, especi…
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…