activity
20102026
most citedEuclid. I. Overview of the Euclid mission

550 citations · 1.4k across the 73 of their papers we have counts for

collaborators
Showing astro-ph.GAShow all

8 papers · 1 filter

astro-ph.GA2024

Euclid preparation. XLIX. Selecting active galactic nuclei using observed colours

Euclid Collaboration, L. Bisigello, M. Massimo +244

Euclid will cover over 14000 with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN)…

astro-ph.GA2024★ 15 cited

Euclid preparation. The Cosmic Dawn Survey (DAWN) of the Euclid Deep and Auxiliary Fields

Euclid Collaboration, C. J. R. McPartland, L. Zalesky +288

Euclid will provide deep NIR imaging to 26.5 AB magnitude over 59 deg in its deep and auxiliary fields. The Cosmic DAWN survey complements the deep Euclid data with…

astro-ph.GA2024★ 8 cited

Euclid preparation. LI. Forecasting the recovery of galaxy physical properties and their relations with template-fitting and machine-learning methods

Euclid Collaboration, A. Enia, M. Bolzonella +260

Euclid will collect an enormous amount of data during the mission's lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting metho…

astro-ph.GA2024★ 7 cited

Euclid preparation. Observational expectations for redshift z<7 active galactic nuclei in the Euclid Wide and Deep surveys

Euclid Collaboration, M. Selwood, S. Fotopoulou +260

We forecast the expected population of active galactic nuclei (AGN) observable in the Euclid Wide Survey (EWS) and Euclid Deep Survey (EDS). Starting from an X-ray luminosity funct…

astro-ph.GA2023

Euclid preparation. Spectroscopy of active galactic nuclei with NISP

Euclid Collaboration, E. Lusso, S. Fotopoulou +246

The statistical distribution and evolution of key properties (e.g. accretion rate, mass, or spin) of active galactic nuclei (AGN), remain an open debate in astrophysics. The ESA Eu…

astro-ph.GA2023★ 15 cited

Euclid Preparation XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong lensing events

Euclid Collaboration, L. Leuzzi, M. Meneghetti +216

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions…