107 citations · 1.1k across the 28 of their papers we have counts for
10 papers · 1 filter
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…
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…
CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop
Pau Tallada, Jorge Carretero, Jordi Casals +13
We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmol…
The PAU Survey: Background light estimation with deep learning techniques
Laura Cabayol-Garcia, Martin B. Eriksen, Àlex Alarcón +17
In any imaging survey, measuring accurately the astronomical background light is crucial to obtain good photometry. This paper introduces BKGnet, a deep neural network to predict t…
The Physics of the Accelerating Universe Camera
Cristobal Padilla, Francisco J. Castander, Alex Alarcon +30
The PAU (Physics of the Accelerating Universe) Survey goal is to obtain photometric redshifts (photo-z) and Spectral Energy Distribution (SED) of astronomical objects with a resolu…