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• Euclid preparation : XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models 

  Euclid Collaboration (EDP Sciences, 2022)

  We present a machine learning framework to simulate realistic galaxies for the Euclid Survey, producing more complex and realistic galaxies than the analytical simulations currently used in Euclid. The proposed method ...

• Euclid preparation : XXII. Selection of quiescent galaxies from mock photometry using machine learning 

  Euclid Collaboration (EDP Sciences, 2023)

  The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15 000deg2 of the sky. Euclid is expected to detect ~12 billion ...

• Euclid preparation : XIX. Impact of magnification on photometric galaxy clustering 

  Euclid Collaboration (EDP Sciences, 2022)

  Aims. We investigate the importance of lensing magnification for estimates of galaxy clustering and its cross-correlation with shear for the photometric sample of Euclid. Using updated specifications, we study the impact ...

• Euclid preparation : XI. Mean redshift determination from galaxy redshift probabilities for cosmic shear tomography 

  Euclid Collaboration (EDP Sciences, 2021)

  The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on an accurate ...

• Euclid preparation : XVII. Cosmic Dawn Survey : Spitzer Space Telescope observations of the Euclid deep fields and calibration fields 

  Euclid Collaboration (EDP Sciences, 2022)

  We present a new infrared survey covering the three Euclid deep fields and four other Euclid calibration fields using Spitzer Space Telescope’s Infrared Array Camera (IRAC). We combined these new observations with all ...