Dependency of high-mass satellite galaxy abundance on cosmology in Magneticum simulations

Context. Observational studies carried out to calibrate the masses of galaxy clusters often use mass-richness relations to interpret galaxy number counts.Aims. Here, we aim to study the impact of the richness-mass relation modelled with cosmological parameters on mock mass calibrations.Methods. We build a Gaussian process regression emulator of high-mass satellite abundance normalisation and log-slope based on cosmological parameters & omega;(m), & omega;(b), & sigma;(8), h(0), and redshift z. We train our emulator using Magneticum hydrodynamic simulations that span different cosmologies for a given set of feedback scheme parameters.Results. We find that the normalisation depends, albeit weakly, on cosmological parameters, especially on & omega;(m) and & omega;(b), and that their inclusion in mock observations increases the constraining power of these latter by 10%. On the other hand, the log-slope is & AP;1 in every setup, and the emulator does not predict it with significant accuracy. We also show that satellite abundance cosmology dependency differs between full-physics simulations, dark-matter only, and non-radiative simulations.Conclusions. Mass-calibration studies would benefit from modelling of the mass-richness relations with cosmological parameters, especially if the satellite abundance cosmology dependency.

Automated summary

This study investigates the impact of the richness-mass relation on mock mass calibrations, using a Gaussian process regression emulator to model the relation with cosmological parameters. The results show that the normalization of the relation has weak dependence on cosmological parameters, particularly the matter density parameter and the baryon density parameter. Including these parameters in mock observations increases their constraining power by 10%.