The cosmological analysis of X-ray cluster surveys

III. 4D X-ray observable diagrams

¹ IRFU, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
e-mail: marguerite.pierre@cea.fr
² Université Paris Diderot, AIM, Sorbonne Paris Cité, CEA, CNRS, 91191 Gif-sur-Yvette, France
³ Max Planck Institut für Extraterrestrische Physik, Giessenbachstrasse 1, 85748 Garching bei München, Germany
⁴ CNRS, IRAP, 9 Av. colonel Roche, 31028 Toulouse Cedex 4, France
⁵ Université de Toulouse, UPS-OMP, IRAP, 31028 Toulouse Cedex 4, France
⁶ Argelander Institut für Astronomie, Universität Bonn, 53121 Bonn, Germany

Received: 21 September 2016
Accepted: 17 August 2017

Abstract

Context. Despite compelling theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties surrounding cluster-mass estimates.

Aims. Our aim is to develop a fully self-consistent cosmological approach of X-ray cluster surveys, exclusively based on observable quantities rather than masses. This procedure is justified given the possibility to directly derive the cluster properties via ab initio modelling, either analytically or by using hydrodynamical simulations. In this third paper, we evaluate the method on cluster toy-catalogues.

Methods. We model the population of detected clusters in the count-rate – hardness-ratio – angular size – redshift space and compare the corresponding four-dimensional diagram with theoretical predictions. The best cosmology+physics parameter configuration is determined using a simple minimisation procedure; errors on the parameters are estimated by averaging the results from ten independent survey realisations. The method allows a simultaneous fit of the cosmological parameters of the cluster evolutionary physics and of the selection effects.

Results. When using information from the X-ray survey alone plus redshifts, this approach is shown to be as accurate as the modelling of the mass function for the cosmological parameters and to perform better for the cluster physics, for a similar level of assumptions on the scaling relations. It enables the identification of degenerate combinations of parameter values.

Conclusions. Given the considerably shorter computer times involved for running the minimisation procedure in the observed parameter space, this method appears to clearly outperform traditional mass-based approaches when X-ray survey data alone are available.