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Euclid preparation
XXXV. Covariance model validation for the two-point correlation function of galaxy clusters

Euclid Collaboration, A. Fumagalli, A. Saro, S. Borgani, T. Castro, M. Costanzi, P. Monaco, E. Munari, E. Sefusatti, A. Le Brun, N. Aghanim, N. Auricchio, M. Baldi, C. Bodendorf, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. Carbone, J. Carretero, F. J. Castander, M. Castellano, S. Cavuoti, R. Cledassou, G. Congedo, C. J. Conselice, L. Conversi, Y. Copin, L. Corcione, F. Courbin, M. Cropper, A. C. da Silva, H. Degaudenzi, F. Dubath, X. Dupac, S. Dusini, S. Farrens, S. Ferriol, M. Frailis, E. Franceschi, P. Franzetti, S. Galeotta, B. Garilli, W. Gillard, B. R. Gillis, C. Giocoli, A. Grazian, F. Grupp, S. V. H. Haugan, W. A. Holmes, A. Hornstrup, P. Hudelot, K. Jahnke, M. Kümmel, S. Kermiche, A. Kiessling, M. Kilbinger, T. D. Kitching, M. Kunz, H. Kurki-Suonio, S. Ligori, P. B. Lilje, I. Lloro, O. Mansutti, O. Marggraf, K. Markovic, F. Marulli, R. Massey, S. Maurogordato, E. Medinaceli, S. Mei, M. Meneghetti, G. Meylan, M. Moresco, L. Moscardini, S. M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, W. J. Percival, V. Pettorino, S. Pires, G. Polenta, M. Poncet, F. Raison, R. Rebolo-Lopez, A. Renzi, J. D. Rhodes, G. Riccio, E. Romelli, M. Roncarelli, R. Saglia, D. Sapone, B. Sartoris, P. C. Schneider, A. Secroun, G. Seidel, C. Sirignano, G. Sirri, L. Stanco, P. Tallada-Crespí, A. N. Taylor, I. Tereno, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, L. Valenziano, T. Vassallo, Y. Wang, J. Weller, A. Zacchei, G. Zamorani, J. Zoubian, S. Andreon, S. Bardelli, A. Boucaud, E. Bozzo, C. Colodro-Conde, D. Di Ferdinando, G. Fabbian, M. Farina, V. Lindholm, D. Maino, N. Mauri, C. Neissner, V. Scottez, E. Zucca, C. Baccigalupi, A. Balaguera-Antolínez, M. Ballardini, F. Bernardeau, A. Biviano, A. Blanchard, A. S. Borlaff, C. Burigana, R. Cabanac, C. S. Carvalho, S. Casas, G. Castignani, K. C. Chambers, A. R. Cooray, J. Coupon, H. M. Courtois, S. Davini, S. de la Torre, G. Desprez, H. Dole, J. A. Escartin, S. Escoffier, P. G. Ferreira, F. Finelli, J. Garcia-Bellido, K. George, G. Gozaliasl, H. Hildebrandt, I. M. Hook, A. Jimenez Muñoz, B. Joachimi, V. Kansal, E. Keihänen, C. C. Kirkpatrick, A. Loureiro, M. Magliocchetti, R. Maoli, S. Marcin, M. Martinelli, N. Martinet, S. Matthew, M. Maturi, L. Maurin, R. B. Metcalf, G. Morgante, S. Nadathur, A. A. Nucita, L. Patrizii, J. E. Pollack, V. Popa, C. Porciani, D. Potter, A. Pourtsidou, M. Pöntinen, A. G. Sánchez, Z. Sakr, M. Schirmer, M. Sereno, A. Spurio Mancini, J. Stadel, J. Steinwagner, C. Valieri, J. Valiviita, A. Veropalumbo, M. Viel

Abstract
Aims. We validate a semi-analytical model for the covariance of the real-space two-point correlation function of galaxy clusters.

Methods
. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrated a simple model to accurately describe the clustering covariance. Then, we used this model to quantify the likelihood-analysis response to variations in the covariance, and we investigated 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 two-point correlation function of galaxy clusters. By introducing a few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with an accuracy of 10%, with differences of about 5% on the figure of merit of the cosmological parameters Ωm and σ8. We also find that the covariance contains additional valuable information that is not present in the mean value, and the constraining power of cluster clustering can improve significantly when its cosmology dependence is accounted for. Finally, we find that the cosmological figure of merit can be further improved when mass binning is taken into account. Our results have significant implications for the derivation of cosmological constraints from the two-point clustering statistics of the Euclid survey of galaxy clusters.

Keywords
methods: statistical / galaxies: clusters: general / cosmological parameters / large-scale structure of Universe

Astronomy & Astrophysics
Volume 683, Article Number A253, Number of pages 19
2024 March

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Faculdade de Ciências da Universidade de Lisboa Universidade do Porto Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Fundação para a Ciência e a Tecnologia COMPETE 2020 PORTUGAL 2020 União Europeia