Euclid preparation: LXVII. Deep learning true galaxy morphologies for weak lensing shear bias calibration
To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double Sérsic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified parametric characterisation. While this approximation may be sufficient for previous data sets, the
Euclid Collaboration et al.
Fecha de publicación:
3
2025