Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters

UNSPECIFIED (2024) Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters. Astronomy and Astrophysics. ISSN 1432-0746 (In Press)

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Abstract

Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrate a simple model to accurately describe the clustering covariance. Then, we use such a model to quantify the likelihood analysis response to variations of the covariance, and investigate the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the 2-point correlation function of galaxy clusters. By introducing few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with 10 per cent accuracy, with differences of about 5 per cent on the figure of merit of the cosmological parameters $\Omega_{\rm m}$ and $\sigma_8$. Also, we find that the cosmology-dependence of the covariance adds valuable information that is not contained in the mean value, significantly improving the constraining power of cluster clustering. Finally, we find that the cosmological figure of merit can be further improved by taking mass binning into account. Our results have significant implications for the derivation of cosmological constraints from the 2-point clustering statistics of the Euclid survey of galaxy clusters.

Item Type:
Journal Article
Journal or Publication Title:
Astronomy and Astrophysics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/3100/3103
Subjects:
?? astrophysics - cosmology and nongalactic astrophysics85a40astronomy and astrophysicsspace and planetary science ??
ID Code:
213052
Deposited By:
Deposited On:
18 Jan 2024 00:29
Refereed?:
Yes
Published?:
In Press
Last Modified:
27 Mar 2024 01:05