The Three Hundred-NIKA2 Sunyaev-Zeldovich Large Program twin samples: Synthetic clusters to support real observations

TL;DR

This paper presents a simulation-based approach to generate synthetic galaxy cluster samples that match real observations, enabling comparison of different mass proxies and improving cluster mass estimates.

Contribution

It introduces twin samples from hydrodynamical simulations that replicate observational properties of galaxy clusters for the NIKA2 SZ Large Program.

Findings

Synthetic clusters match observational parameters like redshift, mass, and $Y_{500}$.

Mock observational maps across multiple wavelengths are generated.

The method allows for cross-calibration of mass proxies and bias reduction.

Abstract

The simulation database of THE THREE HUNDRED Project has been used to pick synthetic clusters of galaxies with properties close to the observational targets of the NIKA2 camera Sunyaev-Zeldovich (SZ) Large Program. Cross-matching of cluster parameters such as mass and redshift of the cluster in the two databases has been implemented to generate the so-called twin samples for the Large Program. This SZ Large Program is observing a selection of galaxy clusters at intermediate and high redshift $\left( 0.5 < z < 0.9 \right)$, covering one order of magnitude in mass. These are SZ-selected clusters from the Planck and Atacama Cosmology Telescope catalogs, wherein the selection is based on their integrated Compton parameter values, $Y_{500}$: the value of the parameter within the characteristics radius $R_{500}$. THE THREE HUNDRED hydrodynamical simulations provide us with hundreds of clusters satisfying these redshift, mass, and $Y_{500}$ requirements. In addition to the standard post-processing analysis of the simulation, mock observational maps are available mimicking X-ray, optical, gravitational lensing, radio, and SZ observations of galaxy clusters. The primary goal of employing the twin samples is to compare different cluster mass proxies from synthetic X-ray, SZ effect and optical maps (via the velocity dispersion of member galaxies and lensing $\kappa$-maps) of the clusters. Eventually, scaling laws between different mass proxies and the cluster mass will be cross-correlated to reduce the scatter on the inferred mass and the mass bias will be related to various physical parameters.