550 citations · 2.8k across the 156 of their papers we have counts for
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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…
Euclid preparation: VII. Forecast validation for Euclid cosmological probes
Euclid Collaboration, A. Blanchard, S. Camera +151
The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. Estimation of…
PySAP: Python Sparse Data Analysis Package for Multidisciplinary Image Processing
S. Farrens, A. Grigis, L. El Gueddari +7
We present the open-source image processing software package PySAP (Python Sparse data Analysis Package) developed for the COmpressed Sensing for Magnetic resonance Imaging and Cos…
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…
Euclid preparation III. Galaxy cluster detection in the wide photometric survey, performance and algorithm selection
Euclid Collaboration, R. Adam, M. Vannier +56
Galaxy cluster counts in bins of mass and redshift have been shown to be a competitive probe to test cosmological models. This method requires an efficient blind detection of clust…