The SRG/eROSITA All-Sky Survey: X-ray selection function models for the eRASS1 galaxy cluster cosmology

Abstract

Characterising galaxy cluster populations from catalog of sources selected in astronomical surveys requires knowledge of sample incompleteness, known as selection function. The first All-Sky Survey (eRASS1) by eROSITA onboard Spectrum Roentgen Gamma (SRG) has enabled the collection of large samples of galaxy clusters detected in the soft X-ray band over the Western Galactic hemisphere. The driving goal consists in constraining cosmological parameters, which puts stringent requirements on accuracy, flexibility and explainability of the selection function models. We use a large set of mock observations of the eRASS1 survey and we process simulated data identically to the real eRASS1 events. We match detected sources to simulated clusters and we associate detections to intrinsic cluster properties. We train a series of models to build selection functions depending only on observable surface brightness data. We develop a second series of models relying on global cluster characteristics such as X-ray luminosity, flux, and expected instrumental count-rate as well as on morphological properties. We validate our models using our simulations and we rank them according to selected performance metrics. We validate the models with datasets of clusters detected in X-rays and via the Sunyaev-Zeldovich effect. We present the complete Bayesian population modelling framework developed for this purpose. Our results reveal the surface brightness characteristics most relevant to cluster selection in the eRASS1 sample, in particular the ambiguous role of central surface brightness at the scale of the instrument resolution. We have produced a series of user-friendly selection function models and demonstrated their validity and their limitations. Our selection function for bright sources reproduces well the catalog matches with external datasets. (abridged)