Characterising galaxy clusters’ completeness function in Planck with hydrodynamical simulations

Abstract

Galaxy cluster number counts are an important probe with which to constrain cosmological parameters. One of the main ingredients of the analysis, along with accurate estimates of cluster masses, is the selection function, and in particular the completeness associated with the cluster sample under consideration. Incorrectly characterising this function can lead to biases in cosmological constraints. In this work, we want to study the completeness of the Planck cluster catalogue, estimating the probability of cluster detection in a realistic setting using hydrodynamical simulations. In particular, we probe the case in which the cluster model assumed in the detection method differs from the shapes and profiles of true galaxy clusters. We created around 9000 images of the Sunyaev–Zel’dovich effect from galaxy clusters from the IllustrisTNG simulation, and used a Monte Carlo injection method to estimate the completeness function. We studied the impact of having different cluster pressure profiles and complex cluster morphologies on the detection process. We find that the cluster profile has a significant effect on completeness, with clusters with steeper profiles producing a higher completeness than ones with flatter profiles. We also show that cluster morphology has a small impact on completeness, finding that elliptical clusters have a slightly lower probability of detection with respect to spherically symmetric ones. Finally, we investigate the impact of a different completeness function on a cosmological analysis with cluster number counts, showing a shift in the constraints on Ωm and σ8 that lies in the same direction as the shift driven by the mass bias.