SZ power spectrum and cluster numbers from an extended merger-tree model

TL;DR

This paper introduces an extended merger-tree model to predict galaxy cluster properties, including the SZ power spectrum and cluster counts, accounting for uncertainties and comparing results with simulations and observations.

Contribution

The paper presents a novel extended merger-tree model that efficiently models hierarchical galaxy cluster evolution and predicts SZ power spectrum and cluster counts with uncertainty analysis.

Findings

Results align with latest SPT measurements under certain assumptions.

Model effectively predicts cluster number counts based on cosmological parameters.

Comparison with simulations validates the model's accuracy.

Abstract

We have recently developed an extended merger-tree model that efficiently follows hierarchical evolution of galaxy clusters and provides a quantitative description of both their dark matter and gas properties. We employed this diagnostic tool to calculate the thermal SZ power spectrum and cluster number counts, accounting explicitly for uncertainties in the relevant statistical and intrinsic cluster properties, such as the halo mass function and the gas equation of state. Results of these calculations are compared with those obtained from a direct analytic treatment and from hydrodynamical simulations. We show that under certain assumptions on the gas mass fraction our results are consistent with the latest SPT measurement. Our approach can be particularly useful in predicting cluster number counts and their dependence on cluster and cosmological parameters.