Abstract
| Original language | English |
|---|---|
| Article number | A253 |
| Number of pages | 19 |
| Journal | Astronomy and Astrophysics |
| Volume | 683 |
| Early online date | 22 Mar 2024 |
| DOIs | |
| Publication status | Published - Mar 2024 |
Keywords
- Cosmological parameters
- Galaxies: clusters: general
- Large-scale structure of Universe
- Methods: statistical
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- 10.48550/arXiv.2211.12965Licence: CC BY
- 10.1051/0004-6361/202245540Licence: CC BY
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In: Astronomy and Astrophysics, Vol. 683, A253, 03.2024.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Euclid preparation
T2 - XXXV. Covariance model validation for the two-point correlation function of galaxy clusters
AU - Fumagalli, A.
AU - Saro, A.
AU - Borgani, S.
AU - Castro, T.
AU - Costanzi, M.
AU - Monaco, P.
AU - Munari, E.
AU - Sefusatti, E.
AU - Le Brun, A. M.C.
AU - Aghanim, N.
AU - Auricchio, N.
AU - Baldi, M.
AU - Bodendorf, C.
AU - Bonino, D.
AU - Branchini, E.
AU - Brescia, M.
AU - Brinchmann, J.
AU - Camera, S.
AU - Capobianco, V.
AU - Carbone, C.
AU - Carretero, J.
AU - Castander, F. J.
AU - Castellano, M.
AU - Cavuoti, S.
AU - Cledassou, R.
AU - Congedo, G.
AU - Conselice, C. J.
AU - Conversi, L.
AU - Copin, Y.
AU - Corcione, L.
AU - Courbin, F.
AU - Cropper, M.
AU - Da Silva, A.
AU - Degaudenzi, H.
AU - Dubath, F.
AU - Dupac, X.
AU - Dusini, S.
AU - Farrens, S.
AU - Ferriol, S.
AU - Frailis, M.
AU - Franceschi, E.
AU - Franzetti, P.
AU - Galeotta, S.
AU - Garilli, B.
AU - Gillard, W.
AU - Gillis, B.
AU - Giocoli, C.
AU - Grazian, A.
AU - Grupp, F.
AU - Haugan, S. V.H.
AU - Holmes, W.
AU - Hornstrup, A.
AU - Hudelot, P.
AU - Jahnke, K.
AU - Kümmel, M.
AU - Kermiche, S.
AU - Kiessling, A.
AU - Kilbinger, M.
AU - Kitching, T.
AU - Kunz, M.
AU - Kurki-Suonio, H.
AU - Ligori, S.
AU - Lilje, P. B.
AU - Lloro, I.
AU - Mansutti, O.
AU - Marggraf, O.
AU - Markovic, K.
AU - Marulli, F.
AU - Massey, R.
AU - Maurogordato, S.
AU - Medinaceli, E.
AU - Mei, S.
AU - Meneghetti, M.
AU - Meylan, G.
AU - Moresco, M.
AU - Moscardini, L.
AU - Niemi, S. M.
AU - Padilla, C.
AU - Paltani, S.
AU - Pasian, F.
AU - Pedersen, K.
AU - Percival, W. J.
AU - Pettorino, V.
AU - Pires, S.
AU - Polenta, G.
AU - Poncet, M.
AU - Raison, F.
AU - Rebolo-Lopez, R.
AU - Renzi, A.
AU - Rhodes, J.
AU - Riccio, G.
AU - Romelli, E.
AU - Roncarelli, M.
AU - Saglia, R.
AU - Sapone, D.
AU - Sartoris, B.
AU - Schneider, P.
AU - Secroun, A.
AU - Seidel, G.
AU - Sirignano, C.
AU - Sirri, G.
AU - Stanco, L.
AU - Tallada-Crespí, P.
AU - Taylor, A. N.
AU - Tereno, I.
AU - Toledo-Moreo, R.
AU - Torradeflot, F.
AU - Tutusaus, I.
AU - Valenziano, L.
AU - Vassallo, T.
AU - Wang, Y.
AU - Weller, J.
AU - Zacchei, A.
AU - Zamorani, G.
AU - Zoubian, J.
AU - Andreon, S.
AU - Bardelli, S.
AU - Boucaud, A.
AU - Bozzo, E.
AU - Colodro-Conde, C.
AU - Di Ferdinando, D.
AU - Fabbian, G.
AU - Farina, M.
AU - Lindholm, V.
AU - Maino, D.
AU - Mauri, N.
AU - Neissner, C.
AU - Scottez, V.
AU - Zucca, E.
AU - Baccigalupi, C.
AU - Balaguera-Antolínez, A.
AU - Ballardini, M.
AU - Bernardeau, F.
AU - Biviano, A.
AU - Blanchard, A.
AU - Borlaff, A. S.
AU - Burigana, C.
AU - Cabanac, R.
AU - Carvalho, C. S.
AU - Casas, S.
AU - Castignani, G.
AU - Chambers, K.
AU - Cooray, A. R.
AU - Coupon, J.
AU - Courtois, H. M.
AU - Davini, S.
AU - De La Torre, S.
AU - Desprez, G.
AU - Dole, H.
AU - Escartin, J. A.
AU - Escoffier, S.
AU - Ferreira, P. G.
AU - Finelli, F.
AU - Garcia-Bellido, J.
AU - George, K.
AU - Gozaliasl, G.
AU - Hildebrandt, H.
AU - Hook, I.
AU - Jimenez Muñoz, A.
AU - Joachimi, B.
AU - Kansal, V.
AU - Keihänen, E.
AU - Kirkpatrick, C. C.
AU - Loureiro, A.
AU - Magliocchetti, M.
AU - Maoli, R.
AU - Marcin, S.
AU - Martinelli, M.
AU - Martinet, N.
AU - Matthew, S.
AU - Maturi, M.
AU - Maurin, L.
AU - Metcalf, R. B.
AU - Morgante, G.
AU - Nadathur, S.
AU - Nucita, A. A.
AU - Patrizii, L.
AU - Pollack, J. E.
AU - Popa, V.
AU - Porciani, C.
AU - Potter, D.
AU - Pourtsidou, A.
AU - Pöntinen, M.
AU - Sánchez, A. G.
AU - Sakr, Z.
AU - Schirmer, M.
AU - Sereno, M.
AU - Spurio Mancini, A.
AU - Stadel, J.
AU - Steinwagner, J.
AU - Valieri, C.
AU - Valiviita, J.
AU - Veropalumbo, A.
AU - Viel, M.
N1 - Publisher Copyright: © 2004 Teaching Mathematics and its Applications. All rights reserved.
PY - 2024/3
Y1 - 2024/3
N2 - 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.
AB - 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.
KW - Cosmological parameters
KW - Galaxies: clusters: general
KW - Large-scale structure of Universe
KW - Methods: statistical
UR - https://www.scopus.com/pages/publications/85185558070
U2 - 10.48550/arXiv.2211.12965
DO - 10.48550/arXiv.2211.12965
M3 - Article
AN - SCOPUS:85185558070
SN - 0004-6361
VL - 683
JO - Astronomy and Astrophysics
JF - Astronomy and Astrophysics
M1 - A253
ER -