Our immediate objectives are the following:

1) Develop new methods which combine strong- and weak-lensing constraints observed in the core and the outskirts of clusters respectively. For this we will make use of the deepest HST data ever obtained on cluster cores as part of the HFF program, together with the recently started BUFFALO observations extending the HST coverage towards the outskirts of the same clusters. These developments include global approaches to model both datasets, as well as the implementation of new non-parametric methods.

2) Combine the precise dark matter mass maps obtained from the combination of strong- and weak-lensing constraints with information on the stars, from HST, and the intra-cluster gas, from XMM-Newton and Chandra space observatories. We will use an improved version of the Bonamigo et al. 2018 (ApJ, 864,98) method to compute the gas mass directly from the X-ray surface brightness, without any assumption of hydro-static equilibrium (see also Para cz et al. 2016 A&A 594 121).

This will give us a global picture of the different mass components of the clusters up to their virial radius, providing unique insights into the physics happening there. Such a unique and high resolution view will allow us to detect all the components that make the clusters, infalling smaller groups and clusters called substructures. These components represent a unique test of the nature of dark matter as different type of dark matter will predict a different number of substructures at a given mass, but also a different amount of gas and stars in them, and possibly different types of interactions between stars, gas and dark matter. By counting and dissecting these substructures and comparing our observational measurements with theoretical predictions from state-of-the-art numerical simulations, we can differentiate between the various types of dark matter.