activity
19952025
most citedKiDS-450: Cosmological parameter constraints from tomographic weak gravitational lensing

1k citations · 5.9k across the 100 of their papers we have counts for

collaborators

108 papers

astro-ph.CO2025

Euclid preparation. XCVIII. Cosmology Likelihood for Observables in Euclid (CLOE). 5: Extensions beyond the standard modelling of theoretical probes and systematic effects

Euclid Collaboration, L. W. K. Goh, A. Nouri-Zonoz +301

Euclid is expected to establish new state-of-the-art constraints on extensions beyond the standard LCDM cosmological model by measuring the positions and shapes of billions of gala…

astro-ph.CO2024★ 3 cited

Euclid preparation. Improving cosmological constraints using a new multi-tracer method with the spectroscopic and photometric samples

Euclid Collaboration, F. Dournac, A. Blanchard +240

Future data provided by the Euclid mission will allow us to better understand the cosmic history of the Universe. A metric of its performance is the figure-of-merit (FoM) of dark e…

astro-ph.CO2024

Euclid preparation. XLII. A unified catalogue-level reanalysis of weak lensing by galaxy clusters in five imaging surveys

Euclid Collaboration, M. Sereno, S. Farrens +221

Precise and accurate mass calibration is required to exploit galaxy clusters as astrophysical and cosmological probes in the Euclid era. Systematic errors in lensing signals by gal…

astro-ph.CO2024★ 3 cited

Euclid: Testing photometric selection of emission-line galaxy targets

M. S. Cagliari, B. R. Granett, L. Guzzo +144

Multi-object spectroscopic galaxy surveys typically make use of photometric and colour criteria to select targets. Conversely, the Euclid NISP slitless spectrograph will record spe…

astro-ph.IM2024

Object classification with Convolutional Neural Networks: from KiDS to Euclid

G. A. Verdoes Kleijn, C. A. Marocico, Y. Mzayek +11

Large-scale imaging surveys have grown about 1000 times faster than the number of astronomers in the last 3 decades. Using Artificial Intelligence instead of astronomer's brains fo…

astro-ph.GA2024★ 17 cited

Euclid preparation. XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning

Euclid Collaboration, B. Aussel, S. Kruk +255

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep…