Euclid: The linear-construction covariance and cosmology

We study the properties of galaxy cluster two-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 used 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 were used to fit a theoretical four-parameter model for the covariance. We then used the two fitted covariance models in a likelihood function to estimate two cosmological parameters -- the matter density parameter Om and the amplitude of the matter density fluctuations σ_8 -- from the simulated mock catalogues. The purpose of this was to validate the LC-covariance-based model against the sample-covariance model. The catalogues were simulated assuming the spatially flat ΛCDM cosmology, with Om = 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 marginalised constraints are Om = 0.307 ± 0.003 and σ_8 = 0.826± 0.009 (sample covariance), and Om = 0.308 ± 0.003 and σ_8 = 0.825 ± 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.

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Publication Details

Journal
Astronomy and Astrophysics
Published
2026-09-17
DOI
https://doi.org/10.1051/0004-6361/202659794
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
0.00

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article

Euclid: The linear-construction covariance and cosmology

Chris Carbone, German Castignani, Martina Kunz, F. Marulli et al.
Astronomy and Astrophysics
Galaxies: Formation, Evolution, Phenomena
article

Euclid: The linear-construction covariance and cosmology

Chris Carbone, German Castignani, Martina Kunz, F. Marulli, J. Carretero, C. Giocoli, Hannu Kurki-Suonio, S. Casas, Pietro Battaglia, F Courbin, S. Andreon, S. Marcin, E. Maiorano, B. Gillis, A. Hornstrup, Marcelo Farina, E. Medinaceli, Pettorino, B. Altieri, F. Pasian, Elina Sihvola, M. Castellano, Mattia Brescia, S. Ferriol, R Farinelli, M. Martinelli, Marion Poncet, Hubert Degaudenzi, Ole Marggraf, Sandro Bardelli, Xavier Dupac, Warren Holmes, Michele Ennio Maria Moresco, P Fosalba, Smain Kermiche, B. Kubik, Nadine Martinet, C Colodro-Conde, Yannick Copin, Luca Conversi, Stephanie Escoffier, Lauro Moscardini, Stefano Cavuoti, Stefano Camera, Sebastiano Ligori, S. Galeotta, O. Mansutti, M. Frailis, S. Mei, M. Melchior, H. M. Courtois, E. Franceschi, M. Baldi, K. Jahnke, C. Neissner, V. F. Cardone, R. Nakajima, A. M. C. Le Brun, R. J. Massey, C. Padilla, H. Dole, G. Meylan, A. Fumagalli, M. Meneghetti, S. -M. Niemi, G. Congedo, G. Mainetti, S. V. H. Haugan, F. Grupp, A. Mora, A. Grazian, I. Lloro, S. Fotopoulou, K. C. Chambers, P. B. Lilje, E. Branchini, K. Pedersen, S. Dusini, G. Polenta, A. Biviano, A. Kiessling, G. De Lucia, A. Cimatti, N. Auricchio, L. A. Popa, S. Pires, V. Lindholm, M. Jhabvala, C. Baccigalupi, J. Valiviita, M. Fumana, F. Finelli, K. George, V. Capobianco, F. Dubath, S. Paltani, F. Hormuth, E. Merlin, J. Gracia-Carpio, A. Da Silva
article en

Abstract

We study the properties of galaxy cluster two-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 used 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 were used to fit a theoretical four-parameter model for the covariance. We then used the two fitted covariance models in a likelihood function to estimate two cosmological parameters -- the matter density parameter Om and the amplitude of the matter density fluctuations σ_8 -- from the simulated mock catalogues. The purpose of this was to validate the LC-covariance-based model against the sample-covariance model. The catalogues were simulated assuming the spatially flat ΛCDM cosmology, with Om = 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 marginalised constraints are Om = 0.307 ± 0.003 and σ_8 = 0.826± 0.009 (sample covariance), and Om = 0.308 ± 0.003 and σ_8 = 0.825 ± 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.

Astronomy and Astrophysics
National Aeronautics and Space Administration, European Space Agency, Magyar Tudományos Akadémia, Agenzia Spaziale Italiana, China Scholarship Council, National Astronomical Observatory of Japan, Agenția Spațială Română, Norsk Romsenter, Fundação para a Ciência e a Tecnologia, Jenny ja Antti Wihurin Rahasto
Openalex Percentile: Top 77%
Galaxies: Formation, Evolution, Phenomena
DOIOpen Access PDFOpenAlex
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