924 citations · 2.2k across the 199 of their papers we have counts for
4 papers · 1 filter
Euclid preparation: VI. Verifying the Performance of Cosmic Shear Experiments
Euclid Collaboration, P. Paykari, T. D. Kitching +128
Our aim is to quantify the impact of systematic effects on the inference of cosmological parameters from cosmic shear. We present an end-to-end approach that introduces sources of…
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…
Euclid preparation: V. Predicted yield of redshift 7<z<9 quasars from the wide survey
Euclid Collaboration, R. Barnett, S. J. Warren +126
We provide predictions of the yield of quasars from the Euclid wide survey, updating the calculation presented in the Euclid Red Book in several ways. We account for revisi…
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…