Dianoga SIDM: Galaxy cluster self-interacting dark matter simulations

Context. Self-interacting dark matter (SIDM) can tackle or alleviate small-scale issues within the cosmological standard model Lambda CDM, and diverse flavours of SIDM can produce unique astrophysical predictions, resulting in different possible signatures which can be used to test these models with dedicated observations of galaxy clusters. Aims. This work aims to assess the impact of dark matter self-interactions on the properties of galaxy clusters. In particular, the goal is to study the angular dependence of the cross section by testing rare (large angle scattering) and frequent (small angle scattering) SIDM models with velocity-dependent cross sections. Methods. We re-simulated six galaxy cluster zoom-in initial conditions with a dark matter-only run and with full-physics set-up simulations that include a self-consistent treatment of baryon physics. We tested the dark matter-only setup and the full physics setup with the collisionless cold dark matter, rare self-interacting dark matter, and frequent self-interacting dark matter models. We then studied their matter density profiles as well as their subhalo population. Results. Our dark matter-only SIDM simulations agree with theoretical models, and when baryons are included in simulations, our SIDM models substantially increase the central density of galaxy cluster cores compared to full-physics simulations using collisionless dark matter. SIDM subhalo suppression in full-physics simulations is milder compared to the one found in the dark matter-only simulations because of the cuspier baryonic potential that prevents subhalo disruption. Moreover, SIDM with small-angle scattering significantly suppresses a larger number of subhaloes compared to large-angle scattering SIDM models. Additionally, SIDM models generate a broader range of subhalo concentration values, including a tail of more diffuse subhaloes in the outskirts of galaxy clusters and a population of more compact subhaloes in the cluster cores.