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

A. Fumagalli*, A. Saro, S. Borgani, T. Castro, M. Costanzi, P. Monaco, E. Munari, E. Sefusatti, A. M.C. Le Brun, N. Aghanim, N. Auricchio, M. Baldi, C. Bodendorf, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. CarboneJ. 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. 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. Gillis, C. Giocoli, A. Grazian, F. Grupp, S. V.H. Haugan, W. Holmes, A. Hornstrup, P. Hudelot, K. Jahnke, M. Kümmel, S. Kermiche, A. Kiessling, M. Kilbinger, T. 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. Rhodes, G. Riccio, E. Romelli, M. Roncarelli, R. Saglia, D. Sapone, B. Sartoris, P. 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. 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. 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

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

5 Downloads (Pure)

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.

Original languageEnglish
Article numberA253
JournalAstronomy and Astrophysics
Volume683
Number of pages19
ISSN0004-6361
DOIs
Publication statusPublished - 2024

Keywords

  • Cosmological parameters
  • Galaxies: clusters: general
  • Large-scale structure of Universe
  • Methods: statistical

Fingerprint

Dive into the research topics of 'Euclid preparation: XXXV. Covariance model validation for the two-point correlation function of galaxy clusters'. Together they form a unique fingerprint.

Cite this