The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as

As part of the Euclid Early Release Observations (ERO) programme, we analysed deep, wide-field imaging from the VIS and NISP instruments of two Milky Way globular clusters (GCs), namely NGC 6254 (M10) and NGC 6397, to look for observational evidence of their dynamical interaction with the Milky Way. We searched for such an interaction in the form

We study the intracluster light (ICL) and intracluster globular clusters (ICGCs) in the nearby Perseus cluster of galaxies using Euclid's Early Release Observations. By modelling the isophotal and iso-density contours, we mapped the distributions and properties of the ICL and ICGCs out to radii of 200-600 kpc (up to ~ 1/3 of the virial radius

The Euclid Early Release Observations (ERO) showcase Euclid's capabilities in advance of its main mission by targeting 17 astronomical objects, including galaxy clusters, nearby galaxies, globular clusters, and star-forming regions. A total of 24 hours of observing time was allocated in the early months of operation, and the scientific community

The Euclid Early Release Observations (ERO) programme targeted the Perseus cluster of galaxies, gathering deep data in the central region of the cluster over 0.7 deg 2, including the cluster core up to 0.25 r 200. The dataset reaches a point-source depth of I E = 28.0 (Y E, J E, H E = 25.3), AB magnitudes at 5 σ with a 0''.16 (0''.48) full width at

We present an analysis of Euclid observations of a 0.6 deg 2 field in the central region of the Fornax galaxy cluster that were acquired during the performance verification phase. With these data, we investigated the potential of Euclid to identify globular clusters (GCs) at 20 Mpc and validated the search methods using artificial GCs and known GCs