Effects of Completeness and Purity on Cluster Dark Energy Constraints
Michel Aguena, Marcos Lima

TL;DR
This paper investigates how the completeness and purity of galaxy cluster samples influence dark energy constraints, demonstrating that self-calibration can still yield competitive results with proper prior knowledge.
Contribution
It introduces a framework for understanding the impact of selection effects on cluster-based dark energy constraints and assesses the benefits of self-calibration and external calibration.
Findings
Self-calibration of selection parameters is feasible with 50% completeness and purity.
Perfect knowledge of selection parameters constrains dark energy to sigma(w)=0.033.
External calibration improves constraints to sigma(w)=0.041.
Abstract
The statistical properties of galaxy clusters can only be used for cosmological purposes if observational effects related to cluster detection are accurately characterized. These effects include the selection function associated to cluster finder algorithms and survey strategy. The importance of the selection becomes apparent when different cluster finders are applied to the same galaxy catalog, producing different cluster samples. We consider parametrized functional forms for the observable-mass relation, its scatter as well as the completeness and purity of cluster samples, and study how prior knowledge on these function parameters affects dark energy constraints derived from cluster statistics. Under the assumption that completeness and purity reach 50 % at masses around 10^{13.5} Msun/h, we find that self-calibration of selection parameters in current and upcoming cluster surveys is…
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