II. Apples to apples $A^2$: cluster selection functions for next-generation surveys
Bego\~na Ascaso, Simona Mei, Jim G. Bartlett, Txitxo Ben\'itez

TL;DR
This paper models and calibrates the cluster selection functions for next-generation optical and infrared surveys like Euclid and LSST, providing insights into their detection capabilities and the relation between observable and theoretical cluster masses.
Contribution
It introduces calibrated cluster selection functions for Euclid and LSST using realistic mock catalogues, including the modeling of the $M^*_{CL}-M_h$ relation and survey detection thresholds.
Findings
Euclid-Optimistic detects clusters with >80% completeness and purity down to $8\times10^{13} h^{-1} M_{\odot}$ up to z<1.
Detection thresholds increase with redshift, with Euclid-Pessimistic and LSST showing higher mass limits.
The cluster selection functions are consistent with negligible redshift evolution and align with existing observational and simulation results.
Abstract
We present the cluster selection function for three of the largest next-generation stage-IV surveys in the optical and infrared: Euclid-Optimistic, Euclid-Pessimistic and the Large Synoptic Survey Telescope (LSST). To simulate these surveys, we use the realistic mock catalogues introduced in the first paper of this series. We detected galaxy clusters using the Bayesian Cluster Finder (BCF) in the mock catalogues. We then modeled and calibrated the total cluster stellar mass observable-theoretical mass () relation using a power law model, including a possible redshift evolution term. We find a moderate scatter of of 0.124, 0.135 and 0.136 for Euclid-Optimistic, Euclid-Pessimistic and LSST, respectively, comparable to other work over more limited ranges of redshift. Moreover, the three datasets are consistent with…
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