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Hauptverfasser: Lindholm, V., Sihvola, E., Valiviita, J., Fumagalli, A., Altieri, B., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Battaglia, P., Biviano, A., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Chambers, K. C., Cimatti, A., Colodro-Conde, C., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dole, H., Dubath, F., Dupac, X., Dusini, S., Escoffier, S., Farina, M., Farinelli, R., Ferriol, S., Finelli, F., Fosalba, P., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., George, K., Gillis, B., Giocoli, C., Gracia-Carpio, J., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Jhabvala, M., Kermiche, S., Kiessling, A., Kubik, B., Kunz, M., Kurki-Suonio, H., Brun, A. M. C. Le, Ligori, S., Lilje, P. B., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Martinelli, M., Martinet, N., Marulli, F., Massey, R. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Mora, A., Moresco, M., Moscardini, L., Nakajima, R., Neissner, C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rosset, C., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Simon, P., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toft, S., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Vassallo, T., Kleijn, G. Verdoes, Wang, Y., Weller, J., Zamorani, G., Zucca, E., Castro, T., Martín-Fleitas, J., Monaco, P., Pezzotta, A., Scottez, V., Sereno, M., Viel, M., Sciotti, D.
Format: Preprint
Veröffentlicht: 2026
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Online-Zugang:https://arxiv.org/abs/2603.10735
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author Lindholm, V.
Sihvola, E.
Valiviita, J.
Fumagalli, A.
Altieri, B.
Andreon, S.
Auricchio, N.
Baccigalupi, C.
Baldi, M.
Bardelli, S.
Battaglia, P.
Biviano, A.
Branchini, E.
Brescia, M.
Camera, S.
Capobianco, V.
Carbone, C.
Cardone, V. F.
Carretero, J.
Casas, S.
Castellano, M.
Castignani, G.
Cavuoti, S.
Chambers, K. C.
Cimatti, A.
Colodro-Conde, C.
Congedo, G.
Conversi, L.
Copin, Y.
Courbin, F.
Courtois, H. M.
Da Silva, A.
Degaudenzi, H.
De Lucia, G.
Dole, H.
Dubath, F.
Dupac, X.
Dusini, S.
Escoffier, S.
Farina, M.
Farinelli, R.
Ferriol, S.
Finelli, F.
Fosalba, P.
Fotopoulou, S.
Frailis, M.
Franceschi, E.
Fumana, M.
Galeotta, S.
George, K.
Gillis, B.
Giocoli, C.
Gracia-Carpio, J.
Grazian, A.
Grupp, F.
Haugan, S. V. H.
Holmes, W.
Hormuth, F.
Hornstrup, A.
Jahnke, K.
Jhabvala, M.
Kermiche, S.
Kiessling, A.
Kubik, B.
Kunz, M.
Kurki-Suonio, H.
Brun, A. M. C. Le
Ligori, S.
Lilje, P. B.
Lloro, I.
Mainetti, G.
Maiorano, E.
Mansutti, O.
Marcin, S.
Marggraf, O.
Martinelli, M.
Martinet, N.
Marulli, F.
Massey, R. J.
Medinaceli, E.
Mei, S.
Melchior, M.
Meneghetti, M.
Merlin, E.
Meylan, G.
Mora, A.
Moresco, M.
Moscardini, L.
Nakajima, R.
Neissner, C.
Niemi, S. -M.
Padilla, C.
Paltani, S.
Pasian, F.
Pedersen, K.
Pettorino, V.
Pires, S.
Polenta, G.
Poncet, M.
Popa, L. A.
Raison, F.
Renzi, A.
Rhodes, J.
Riccio, G.
Romelli, E.
Roncarelli, M.
Rosset, C.
Saglia, R.
Sakr, Z.
Sánchez, A. G.
Sapone, D.
Schneider, P.
Schrabback, T.
Secroun, A.
Seidel, G.
Simon, P.
Sirignano, C.
Sirri, G.
Stanco, L.
Tallada-Crespí, P.
Taylor, A. N.
Tereno, I.
Toft, S.
Toledo-Moreo, R.
Torradeflot, F.
Tutusaus, I.
Vassallo, T.
Kleijn, G. Verdoes
Wang, Y.
Weller, J.
Zamorani, G.
Zucca, E.
Castro, T.
Martín-Fleitas, J.
Monaco, P.
Pezzotta, A.
Scottez, V.
Sereno, M.
Viel, M.
Sciotti, D.
author_facet Lindholm, V.
Sihvola, E.
Valiviita, J.
Fumagalli, A.
Altieri, B.
Andreon, S.
Auricchio, N.
Baccigalupi, C.
Baldi, M.
Bardelli, S.
Battaglia, P.
Biviano, A.
Branchini, E.
Brescia, M.
Camera, S.
Capobianco, V.
Carbone, C.
Cardone, V. F.
Carretero, J.
Casas, S.
Castellano, M.
Castignani, G.
Cavuoti, S.
Chambers, K. C.
Cimatti, A.
Colodro-Conde, C.
Congedo, G.
Conversi, L.
Copin, Y.
Courbin, F.
Courtois, H. M.
Da Silva, A.
Degaudenzi, H.
De Lucia, G.
Dole, H.
Dubath, F.
Dupac, X.
Dusini, S.
Escoffier, S.
Farina, M.
Farinelli, R.
Ferriol, S.
Finelli, F.
Fosalba, P.
Fotopoulou, S.
Frailis, M.
Franceschi, E.
Fumana, M.
Galeotta, S.
George, K.
Gillis, B.
Giocoli, C.
Gracia-Carpio, J.
Grazian, A.
Grupp, F.
Haugan, S. V. H.
Holmes, W.
Hormuth, F.
Hornstrup, A.
Jahnke, K.
Jhabvala, M.
Kermiche, S.
Kiessling, A.
Kubik, B.
Kunz, M.
Kurki-Suonio, H.
Brun, A. M. C. Le
Ligori, S.
Lilje, P. B.
Lloro, I.
Mainetti, G.
Maiorano, E.
Mansutti, O.
Marcin, S.
Marggraf, O.
Martinelli, M.
Martinet, N.
Marulli, F.
Massey, R. J.
Medinaceli, E.
Mei, S.
Melchior, M.
Meneghetti, M.
Merlin, E.
Meylan, G.
Mora, A.
Moresco, M.
Moscardini, L.
Nakajima, R.
Neissner, C.
Niemi, S. -M.
Padilla, C.
Paltani, S.
Pasian, F.
Pedersen, K.
Pettorino, V.
Pires, S.
Polenta, G.
Poncet, M.
Popa, L. A.
Raison, F.
Renzi, A.
Rhodes, J.
Riccio, G.
Romelli, E.
Roncarelli, M.
Rosset, C.
Saglia, R.
Sakr, Z.
Sánchez, A. G.
Sapone, D.
Schneider, P.
Schrabback, T.
Secroun, A.
Seidel, G.
Simon, P.
Sirignano, C.
Sirri, G.
Stanco, L.
Tallada-Crespí, P.
Taylor, A. N.
Tereno, I.
Toft, S.
Toledo-Moreo, R.
Torradeflot, F.
Tutusaus, I.
Vassallo, T.
Kleijn, G. Verdoes
Wang, Y.
Weller, J.
Zamorani, G.
Zucca, E.
Castro, T.
Martín-Fleitas, J.
Monaco, P.
Pezzotta, A.
Scottez, V.
Sereno, M.
Viel, M.
Sciotti, D.
contents We study the properties of galaxy cluster 2-point correlation function covariance matrices estimated using the linear-construction (LC) method, which is computationally up to 20 times faster than the standard sample-covariance method. Our goal is to assess how well the LC method performs in cosmological parameter estimation compared to the sample covariance. We use a set of 1000 mock dark matter halo catalogues to compute both the LC-covariance and the sample-covariance estimates in four redshift shells. These numerical matrices are used to fit a theoretical four-parameter model for the covariance. We then use the two fitted covariance models in a likelihood function to estimate two cosmological parameters - the matter density parameter $Ω_{\rm m}$ and the amplitude of the matter density fluctuations $σ_8$ - from the simulated mock catalogues. The purpose of this is to validate the LC-covariance-based model against the sample-covariance model. The catalogues were simulated assuming the spatially flat $Λ$CDM cosmology, with $Ω_{\rm m} = 0.30711$ and $σ_8=0.8288$. We find that the parameter posteriors obtained using the sample- and LC-covariance models agree well with each other and with the simulation cosmology. The two pairs of marginalized constraints are $Ω_{\rm m} = 0.307 \pm 0.003$ and $σ_8 = 0.826\pm 0.009$ (sample covariance), and $Ω_{\rm m} = 0.308 \pm 0.003$ and $σ_8 = 0.825 \pm 0.009$ (LC covariance). The posterior widths are the same, and the difference in the median values is less than $0.16\,σ$ for both parameters.
format Preprint
id arxiv_https___arxiv_org_abs_2603_10735
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Euclid: The linear-construction covariance and cosmology
Lindholm, V.
Sihvola, E.
Valiviita, J.
Fumagalli, A.
Altieri, B.
Andreon, S.
Auricchio, N.
Baccigalupi, C.
Baldi, M.
Bardelli, S.
Battaglia, P.
Biviano, A.
Branchini, E.
Brescia, M.
Camera, S.
Capobianco, V.
Carbone, C.
Cardone, V. F.
Carretero, J.
Casas, S.
Castellano, M.
Castignani, G.
Cavuoti, S.
Chambers, K. C.
Cimatti, A.
Colodro-Conde, C.
Congedo, G.
Conversi, L.
Copin, Y.
Courbin, F.
Courtois, H. M.
Da Silva, A.
Degaudenzi, H.
De Lucia, G.
Dole, H.
Dubath, F.
Dupac, X.
Dusini, S.
Escoffier, S.
Farina, M.
Farinelli, R.
Ferriol, S.
Finelli, F.
Fosalba, P.
Fotopoulou, S.
Frailis, M.
Franceschi, E.
Fumana, M.
Galeotta, S.
George, K.
Gillis, B.
Giocoli, C.
Gracia-Carpio, J.
Grazian, A.
Grupp, F.
Haugan, S. V. H.
Holmes, W.
Hormuth, F.
Hornstrup, A.
Jahnke, K.
Jhabvala, M.
Kermiche, S.
Kiessling, A.
Kubik, B.
Kunz, M.
Kurki-Suonio, H.
Brun, A. M. C. Le
Ligori, S.
Lilje, P. B.
Lloro, I.
Mainetti, G.
Maiorano, E.
Mansutti, O.
Marcin, S.
Marggraf, O.
Martinelli, M.
Martinet, N.
Marulli, F.
Massey, R. J.
Medinaceli, E.
Mei, S.
Melchior, M.
Meneghetti, M.
Merlin, E.
Meylan, G.
Mora, A.
Moresco, M.
Moscardini, L.
Nakajima, R.
Neissner, C.
Niemi, S. -M.
Padilla, C.
Paltani, S.
Pasian, F.
Pedersen, K.
Pettorino, V.
Pires, S.
Polenta, G.
Poncet, M.
Popa, L. A.
Raison, F.
Renzi, A.
Rhodes, J.
Riccio, G.
Romelli, E.
Roncarelli, M.
Rosset, C.
Saglia, R.
Sakr, Z.
Sánchez, A. G.
Sapone, D.
Schneider, P.
Schrabback, T.
Secroun, A.
Seidel, G.
Simon, P.
Sirignano, C.
Sirri, G.
Stanco, L.
Tallada-Crespí, P.
Taylor, A. N.
Tereno, I.
Toft, S.
Toledo-Moreo, R.
Torradeflot, F.
Tutusaus, I.
Vassallo, T.
Kleijn, G. Verdoes
Wang, Y.
Weller, J.
Zamorani, G.
Zucca, E.
Castro, T.
Martín-Fleitas, J.
Monaco, P.
Pezzotta, A.
Scottez, V.
Sereno, M.
Viel, M.
Sciotti, D.
Cosmology and Nongalactic Astrophysics
We study the properties of galaxy cluster 2-point correlation function covariance matrices estimated using the linear-construction (LC) method, which is computationally up to 20 times faster than the standard sample-covariance method. Our goal is to assess how well the LC method performs in cosmological parameter estimation compared to the sample covariance. We use a set of 1000 mock dark matter halo catalogues to compute both the LC-covariance and the sample-covariance estimates in four redshift shells. These numerical matrices are used to fit a theoretical four-parameter model for the covariance. We then use the two fitted covariance models in a likelihood function to estimate two cosmological parameters - the matter density parameter $Ω_{\rm m}$ and the amplitude of the matter density fluctuations $σ_8$ - from the simulated mock catalogues. The purpose of this is to validate the LC-covariance-based model against the sample-covariance model. The catalogues were simulated assuming the spatially flat $Λ$CDM cosmology, with $Ω_{\rm m} = 0.30711$ and $σ_8=0.8288$. We find that the parameter posteriors obtained using the sample- and LC-covariance models agree well with each other and with the simulation cosmology. The two pairs of marginalized constraints are $Ω_{\rm m} = 0.307 \pm 0.003$ and $σ_8 = 0.826\pm 0.009$ (sample covariance), and $Ω_{\rm m} = 0.308 \pm 0.003$ and $σ_8 = 0.825 \pm 0.009$ (LC covariance). The posterior widths are the same, and the difference in the median values is less than $0.16\,σ$ for both parameters.
title Euclid: The linear-construction covariance and cosmology
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2603.10735