550 citations · 2.1k across the 171 of their papers we have counts for
8 papers · 1 filter
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…
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…
Euclid: Calibrating photometric redshifts with spectroscopic cross-correlations
K. Naidoo, H. Johnston, B. Joachimi +126
Cosmological constraints from key probes of the Euclid imaging survey rely critically on the accurate determination of the true redshift distributions, , of tomographic redsh…
Euclid preparation. XXIV. Calibration of the halo mass function in CDM cosmologies
Euclid Collaboration, T. Castro, A. Fumagalli +179
Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number…
Euclid: Testing the Copernican principle with next-generation surveys
D. Camarena, V. Marra, Z. Sakr +112
The Copernican principle, the notion that we are not at a special location in the Universe, is one of the cornerstones of modern cosmology and its violation would invalidate the Fr…
Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images
Euclid Collaboration, L. Bisigello, C. J. Conselice +196
Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Ma…