1.2k citations · 29.5k across the 446 of their papers we have counts for
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Dimensional reduction for sampled priors and application to photometric redshift distributions
Gary Bernstein, William Assignies Doumerg, Michael A. Troxel +35
A typical Bayesian inference on the values of some parameters of interest from some data involves running a Markov Chain (MC) to sample from the posterior $p({\bf q},{\…
The Dark Energy Survey Six-Year Calibration Star Catalog
E. S. Rykoff, D. L. Tucker, D. L. Burke +64
This Technical Note presents a catalog of calibrated reference stars that was generated by the Forward Calibration Method (FGCM) pipeline (arXiv:1706.01542) as part of the FGCM pho…
The DECam Local Volume Exploration Survey Data Release 2
A. Drlica-Wagner, P. S. Ferguson, M. Adamów +121
We present the second public data release (DR2) from the DECam Local Volume Exploration survey (DELVE). DELVE DR2 combines new DECam observations with archival DECam data from the…
The Dark Energy Survey Data Release 2
DES Collaboration, T. M. C. Abbott, M. Adamow +132
We present the second public data release of the Dark Energy Survey, DES DR2, based on optical/near-infrared imaging by the Dark Energy Camera mounted on the 4-m Blanco telescope a…
Dark Energy Survey Year 3 Results: Point-Spread Function Modeling
M. Jarvis, G. M. Bernstein, A. Amon +79
We introduce a new software package for modeling the point-spread function (PSF) of astronomical images, called Piff (PSFs In the Full FOV), which we apply to the first three years…
Reducing ground-based astrometric errors with Gaia and Gaussian processes
W. F. Fortino, G. M. Bernstein, P. H. Bernardinelli +64
Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable…
Noise from Undetected Sources in Dark Energy Survey Images
K. Eckert, G. M. Bernstein, A. Amara +66
For ground-based optical imaging with current CCD technology, the Poisson fluctuations in source and sky background photon arrivals dominate the noise budget and are readily estima…
First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Photometric Pipeline and Light Curve Data Release
D. Brout, M. Sako, D. Scolnic +89
We present griz light curves of 251 Type Ia Supernovae (SNe Ia) from the first 3 years of the Dark Energy Survey Supernova Program's (DES-SN) spectroscopically classified sample. T…
Star-galaxy classification in the Dark Energy Survey Y1 dataset
I. Sevilla-Noarbe, B. Hoyle, M. J. Marchã +75
We perform a comparison of different approaches to star-galaxy classification using the broad-band photometric data from Year 1 of the Dark Energy Survey. This is done by performin…
How Many Kilonovae Can Be Found in Past, Present, and Future Survey Datasets?
D. Scolnic, R. Kessler, D. Brout +83
The discovery of a kilonova (KN) associated with the Advanced LIGO (aLIGO)/Virgo event GW170817 opens up new avenues of multi-messenger astrophysics. Here, using realistic simulati…
DES Science Portal: Creating Science-Ready Catalogs
Angelo Fausti Neto, Luiz da Costa, Aurelio Carnero Rosell +55
We present a novel approach for creating science-ready catalogs through a software infrastructure developed for the Dark Energy Survey (DES). We integrate the data products release…
Forward Global Photometric Calibration of the Dark Energy Survey
D. Burke, E. S. Rykoff, S. Allam +56
Many scientific goals for the Dark Energy Survey (DES) require calibration of optical/NIR broadband photometry that is stable in time and uniform over the celestial sky…
COSMOGRAIL XVI: Time delays for the quadruply imaged quasar DES J0408-5354 with high-cadence photometric monitoring
F. Courbin, V. Bonvin, E. Buckley-Geer +74
We present time-delay measurements for the new quadruply imaged quasar DES J0408-5354, the first quadruply imaged quasar found in the Dark Energy Survey (DES). Our result is made p…
Astrometric calibration and performance of the Dark Energy Camera
G. M. Bernstein, R. Armstrong, A. A. Plazas +53
We characterize the ability of the Dark Energy Camera (DECam) to perform relative astrometry across its 500~Mpix, 3 deg^2 science field of view, and across 4 years of operation. Th…
The Astropy Problem
Demitri Muna, Michael Alexander, Alice Allen +151
The Astropy Project (http://astropy.org) is, in its own words, "a community effort to develop a single core package for Astronomy in Python and foster interoperability between Pyth…
Assessment of Systematic Chromatic Errors that Impact Sub-1% Photometric Precision in Large-Area Sky Surveys
T. S. Li, D. L. DePoy, J. L. Marshall +69
Meeting the science goals for many current and future ground-based optical large-area sky surveys requires that the calibrated broadband photometry is stable in time and uniform ov…
Crowdsourcing quality control for Dark Energy Survey images
P. Melchior, E. Sheldon, A. Drlica-Wagner +47
We have developed a crowdsourcing web application for image quality control employed by the Dark Energy Survey. Dubbed the "DES exposure checker", it renders science-grade images d…
redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data
E. Rozo, E. S. Rykoff, A. Abate +84
We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in…
The DES Science Verification Weak Lensing Shear Catalogues
M. Jarvis, E. Sheldon, J. Zuntz +92
We present weak lensing shear catalogues for 139 square degrees of data taken during the Science Verification (SV) time for the new Dark Energy Camera (DECam) being used for the Da…
The Dark Energy Camera
B. Flaugher, H. T. Diehl, K. Honscheid +115
The Dark Energy Camera is a new imager with a 2.2-degree diameter field of view mounted at the prime focus of the Victor M. Blanco 4-meter telescope on Cerro Tololo near La Serena,…
Automated Transient Identification in the Dark Energy Survey
D. A. Goldstein, C. B. D'Andrea, J. A. Fischer +64
We describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. T…
Modelling the Transfer Function for the Dark Energy Survey
C. Chang, M. T. Busha, R. H. Wechsler +40
We present a forward-modelling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfe…