924 citations · 9k across the 382 of their papers we have counts for
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Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters
Euclid Collaboration, A. Fumagalli, A. Saro +191
Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the…
Euclid: Modelling massive neutrinos in cosmology -- a code comparison
J. Adamek, R. E. Angulo, C. Arnold +133
The measurement of the absolute neutrino mass scale from cosmological large-scale clustering data is one of the key science goals of the Euclid mission. Such a measurement relies o…
New applications of Graph Neural Networks in Cosmology
Farida Farsian, Federico Marulli, Lauro Moscardini +1
Upcoming cosmological surveys will provide unprecedented amount of data, which will require innovative statistical methods to maximize the scientific exploitation. Standard cosmolo…
Exploring the cosmological synergy between galaxy cluster and cosmic void number counts
Davide Pelliciari, Sofia Contarini, Federico Marulli +4
Galaxy clusters and cosmic voids, the most extreme objects of our Universe in terms of mass and size, trace two opposite sides of the large-scale matter density field. By studying…
Euclid preparation. XXV. The Euclid Morphology Challenge -- Towards model-fitting photometry for billions of galaxies
Euclid Collaboration, E. Merlin, M. Castellano +218
The ESA Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real…
The PAU Survey & Euclid: Improving broad-band photometric redshifts with multi-task learning
L. Cabayol, M. Eriksen, J. Carretero +123
Current and future imaging surveys require photometric redshifts (photo-zs) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge but is need…