Triaxiality in galaxy clusters: Mass versus potential reconstructions

Abstract

Context. Accounting for the triaxial shapes of galaxy clusters will become important in the context of upcoming cosmological surveys. This will provide a challenge given that the density distribution of gas cannot be described by simple geometrical models without loss of information. Aims. We investigate the effects of simple 3D models on cluster gravitational potentials and gas density distribution to determine which of these quantities is most suitable and appropriate for characterising galaxy clusters in cosmological studies. Methods. We use a statistical sample of 85 galaxy clusters from a large cosmological N-body + hydrodynamical simulation to investigate cluster shapes as a function of radius for both gas density and potential. We examine how the resulting parameters are affected by the substructure removal (for the gas density) and by the definition of the computation volume (interior vs. shells). Results. We find that the orientation and axis ratio of gas isodensity contours are degenerate with the presence of substructures and are unstable against fluctuations. Moreover, as the derived cluster shape depends on the method used for removing the substructures, thermodynamic properties extracted from the X-ray emissivity profile, for example, suffer from this additional and often underestimated bias. In contrast, the shapes of the smooth cluster potentials are less affected by fluctuations and converge towards simple geometrical models, both in the case of relaxed and dynamically active clusters. Conclusions. The observation that cluster potentials can be represented better by simple geometrical models and reconstructed with a lower level of systematic error for both dynamically active and relaxed clusters suggests that characterising galaxy clusters by their potential is a promising alternative to using cluster masses in cluster cosmology. With this approach, dynamically active and relaxed clusters could be combined in cosmological studies, improving statistics and lowering scatter.