Weak lensing, which is the deflection of light by matter along the line of sight, has proven to be an efficient method for constraining models of structure formation and reveal the nature of dark energy. So far, most weak-lensing studies have focused on the shear field that can be measured directly from the ellipticity of background galaxies. However, within the context of forthcoming full-sky weak-lensing surveys such as Euclid, convergence maps (mass maps) offer an important advantage over shear fields in terms of cosmological exploitation. While it carry the same information, the lensing signal is more compressed in the convergence maps than in the shear field. This simplifies otherwise computationally expensive analyses, for instance, non-Gaussianity studies. However, the inversion of the non-local shear field requires accurate control of systematic effects caused by holes in the data field, field borders, shape noise, and the fact that the shear is not a direct observable (reduced shear). We present the two mass-inversion methods that are included in the official Euclid data-processing pipeline: the standard Kaiser & Squires method (KS), and a new mass-inversion method (KS+) that aims to reduce the information loss during the mass inversion. This new method is based on the KS method and includes corrections for mass-mapping systematic effects. The results of the KS+ method are compared to the original implementation of the KS method in its simplest form, using the Euclid Flagship mock galaxy catalogue. In particular, we estimate the quality of the reconstruction by comparing the two-point correlation functions and third- and fourth-order moments obtained from shear and convergence maps, and we analyse each systematic effect independently and simultaneously. We show that the KS+ method substantially reduces the errors on the two-point correlation function and moments compared to the KS method. In particular, we show that the errors introduced by the mass inversion on the two-point correlation of the convergence maps are reduced by a factor of about 5, while the errors on the third- and fourth-order moments are reduced by factors of about 2 and 10, respectively.

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 relevant IRAC archival data of these fields in order to produce the deepest possible mosaics of these regions. In total, these observations represent nearly 11 % of the total Spitzer Space Telescope mission time. The resulting mosaics cover a total of approximately 71.5 deg 2 in the 3.6 and 4.5 µm bands, and approximately 21.8 deg 2 in the 5.8 and 8 µm bands. They reach at least 24 AB magnitude (measured to 5σ, in a 2 . 5 aperture) in the 3.6 µm band and up to ∼ 5 mag deeper in the deepest regions. The astrometry is tied to the Gaia astrometric reference system, and the typical astrometric uncertainty for sources with 16 < [3.6] < 19 is 0 . 15. The photometric calibration is in excellent agreement with previous WISE measurements. We extracted source number counts from the 3.6 µm band mosaics, and they are in excellent agreement with previous measurements. Given that the Spitzer Space Telescope has now been decommissioned, these mosaics are likely to be the definitive reduction of these IRAC data. This survey therefore represents an essential first step in assembling multi-wavelength data on the Euclid deep fields, which are set to become some of the premier fields for extragalactic astronomy in the 2020s.

The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid-detected galaxies and to help implement measurements in the pipeline of the Organisational Unit MER of the Euclid Science Ground Segment, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper focusses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes, DeepLeGATo, Galapagos-2, Morfometryka, ProFitand SourceXtractor++ , on a sample of about 1.5 million simulated galaxies (350 000 above 5σ) resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic Sérsic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements (< 10% scatter on ideal Sérsic simulations) down to an apparent magnitude of about I E = 23 in one component and I E = 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5, respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the official Euclid Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters.