Galaxy cluster number counts with individual lensing mass estimates: forecasts for Euclid

TL;DR

This paper develops a framework for analyzing future Euclid-like galaxy cluster catalogs using individual lensing mass estimates, enabling precise cosmological constraints from upcoming surveys.

Contribution

It introduces a cluster likelihood based on individual masses and demonstrates its effectiveness using simulations for Euclid-like data.

Findings

Joint calibration of the observable mass relation is feasible within this framework.

The matched filter approach accurately estimates weak lensing masses.

The framework is validated with the Flagship N-body simulation.

Abstract

Gradually, the $\Lambda$CDM model starts to be challenged by observational data. Upcoming cosmological surveys will increase the number of detected galaxy clusters by several orders of magnitude. Therefore, shortly, clusters will provide tremendous constraints on cosmology and sharpen our understanding of structure formation. However, a reliable framework is required to analyse future Euclid-like catalogs. We build a cluster likelihood based on individual masses and forecast Euclid performances within this framework. We use a matched filter for weak lensing mass estimation and model its characteristics with a set of simulations. We use the Flagship N-body simulation to emulate the expected cluster mass distribution of a Euclid-like sample and test our statistical framework against it. We prove that the joint callibration of the observable mass relation within this match filtering framework is possible.