5 citations · 6 across the 9 of their papers we have counts for
134 papers
Euclid Quick Data Release (Q1). The average far-infrared properties of Euclid-selected star-forming galaxies
Euclid Collaboration, R. Hill, A. Abghari +302
The first Euclid Quick Data Release contains millions of galaxies with excellent optical and near-infrared (IR) coverage. To complement this dataset, we investigate the average far…
Euclid Quick Data Release (Q1). Searching for radio-selected \Euclid-dark galaxies in the EDF-N
Euclid Collaboration, M. Giulietti, I. Prandoni +308
We present and investigate the properties of a sample of radio-selected, Euclid-dark galaxies, identified from LOFAR HBA observations at 144 MHz within the Euclid Deep Field-North…
Euclid preparation. First investigation of the impact of cross-contamination on spectroscopic redshift measurements with pixel-level simulations
Euclid Collaboration, F. Passalacqua, S. Anselmi +299
We present a study on simulated data focused on understanding the performance of the spectroscopic redshift measurements with the Near-Infrared Spectrometer and Photometer (NISP) i…
Euclid preparation. CIV. Impact of galaxy intrinsic alignment modelling choices on Euclid 3x2pt cosmology
Euclid Collaboration, D. Navarro-Gironés, I. Tutusaus +274
The Euclid galaxy survey will provide unprecedented constraints on cosmology, but achieving unbiased results will require an optimal characterisation and mitigation of systematic e…
Euclid Quick Data Release (Q1): The impact of AGN emission on SED-derived physical properties
Euclid Collaboration, B. Laloux, A. Bongiorno +309
The Euclid Quick Data Release (Q1) is a powerful dataset to study active galactic nuclei (AGN) and their host galaxies. Deriving their physical properties through multi-component s…
Euclid preparation. CII. Non-Gaussianity of 2-pt statistics likelihood: Parameter inference with a non-Gaussian likelihood in Fourier and configuration space
Euclid Collaboration, S. Gouyou Beauchamps, J. Bel +277
In this work we account for this skewness in parameter inference by modelling the likelihood through an Edgeworth expansion which involves the complete skewness tensor, composed of…