Mock galaxy catalogues are often constructed from dark-matter-only simulations based on the galaxy–halo connection. Although modern mocks can reproduce galaxy clustering to some extent, the absence of baryons affects the spatial and kinematic distributions of galaxies in ways that remain insufficiently quantified. We compare the positions and velocities of satellite galaxies in the MTNG hydrodynamic simulation — a state-of-the-art cosmological hydrodynamic run — with those in its dark-matter-only counterpart, assessing how baryonic effects influence galaxy clustering and contrasting them with the impact of galaxy selection, i.e. the dependence of clustering on sample definition. We introduce a new method to track subhaloes using the merger trees of the simulations, which enables us to match systems even when their positions at z=0 differ. We then compute positional and velocity offsets as functions of halo mass and distance from the halo centre, and use these to construct a subhalo catalogue from the dark-matter-only simulation that reproduces the galaxy distribution in the hydrodynamic run. Satellites in the hydrodynamic simulation lie 3–4% closer to halo centres than in the dark-matter-only case, with an offset that is nearly constant with halo mass and increases towards smaller radii. Satellite velocities are also systematically higher in the dark-matter-only run, with differences that grow towards lower halo masses and radii. At scales of 0.1 hMpc, these spatial and kinematic differences produce 10–20% variations in clustering amplitude—corresponding to 1–3σ assuming DESI-like errors—though the impact decreases at larger scales. We repeat the analysis in zoom-in simulations with varied physical models and find consistent trends. These baryonic effects are relevant for cosmological and lensing analyses and should be accounted for when building high-fidelity mocks. However, they remain smaller than the differences introduced by galaxy selection, which thus represents the dominant source of uncertainty when constructing mocks based on observable quantities.
Contreras et al. (Wed,) studied this question.