Merging luminous galaxies are ideal laboratories for studying some of the most extreme astrophysical phenomena. The local (z = 0.1232) obscured quasar J1356+1026 has two nuclei, North and South (J1356N and J1356S), but despite numerous efforts, J1356S had not yet been confirmed as an AGN. Based on the superb sensitivity and spatial resolution of

Polarization at millimeter wavelengths provides a powerful diagnostic of dust grain properties in protoplanetary disks. Standard models based on solid spherical grains often struggle to reproduce the observed polarization fractions and morphologies in systems where self-scattering is expected to dominate. We investigate the impact of grain

Context. The performance of the Euclid system is defined in terms of image quality metrics tuned to the weak gravitational lensing cosmological probe. The weak lensing measurement induces stringent requirements on the shape and stability of the VIS instrument system point spread function (PSF). The PSF is affected by error contributions from the

This study explores the impact of observational and modelling systematic effects on cluster number counts and cluster clustering and provides model prescriptions for their joint analysis in the context of the Euclid survey. Using 1000 Euclid-like cluster catalogues, we investigated the effect of systematic uncertainties on cluster summary

The Euclid mission of the European Space Agency seeks to understand the Universe's expansion history and the nature of dark energy, through measurements of cosmic shear. This requires a very accurate estimate of the true redshift distribution of the galaxies, with the systematic error in the mean redshift satisfying σ ⟨z⟩ < 0.002(1 + z) per

We present an example cluster follow-up study with Euclid. Our target, a z ∼ 1.74 candidate cluster nicknamed the 'Puddle', was initially discovered by the Massive and Distant Clusters of WISE Survey 2 as a z phot ∼ 1.65 candidate cluster. It was also detected independently as a z phot ∼ 1.5 candidate with the two cluster-finding algorithms in