The cosmological analysis of X-ray cluster surveys; III. 4D X-ray observable diagrams

TL;DR

This paper introduces a novel, self-consistent method for cosmological analysis of X-ray cluster surveys that relies solely on observable quantities, improving accuracy and efficiency over traditional mass-based methods.

Contribution

The authors develop and validate a new approach that uses observable data to simultaneously constrain cosmology, cluster physics, and selection effects, avoiding uncertainties in mass estimates.

Findings

Method matches the accuracy of mass function approaches for cosmological parameters.

It outperforms traditional methods in computational efficiency.

It effectively identifies parameter degeneracies.

Abstract

Despite compelling theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties impinging on cluster mass estimates. 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. We model the population of detected clusters in the count-rate -- hardness-ratio -- angular size -- redshift space and compare the corresponding 4-dimensional diagram with theoretical predictions. The best cosmology+physics parameter configuration is determined using a simple minimisation procedure; errors on the parameters are derived by scanning the likelihood hyper-surfaces with a wide range of starting values. The method allows a simultaneous fit of the cosmological parameters, of the cluster evolutionary physics and of the selection effects. When using information from the X-ray survey alone plus redshifts, this approach is shown to be as accurate as the mass function for the cosmological parameters and to perform better for the cluster physics, as modelled in the scaling relations. It enables the identification of degenerate combinations of parameter values. 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.