Comparing approximate methods for mock catalogues and covariance matrices - I. Correlation function
| العنوان: | Comparing approximate methods for mock catalogues and covariance matrices - I. Correlation function |
|---|---|
| المؤلفون: | Marcelo A. Alvarez, Aniket Agrawal, Emiliano Sefusatti, Sandrine Codis, Martin Crocce, Manuel Colavincenzo, Albert Izard, Antonio Dorta, Ariel G. Sánchez, Linda Blot, Marcos Pellejero-Ibanez, George Stein, Richard J. Bond, Santiago Avila, A. Balaguera-Antolínez, Martha Lippich, Gustavo Yepes, Claudio Dalla Vecchia, Francisco-Shu Kitaura, Pierluigi Monaco, Pablo Fosalba, Mohammadjavad Vakili |
| المساهمون: | ITA, FRA, DEU, ESP, CAN, Lippich, Martha, Sánchez, Ariel G, Colavincenzo, Manuel, Sefusatti, Emiliano, Monaco, Pierluigi, Blot, Linda, Crocce, Martin, Alvarez, Marcelo A, Agrawal, Aniket, Avila, Santiago, Balaguera-Antolínez, André, Bond, Richard, Codis, Sandrine, Dalla vecchia, Claudio, Dorta, Antonio, Fosalba, Pablo, Izard, Albert, Kitaura, Francisco-Shu, Pellejero-Ibanez, Marco, Stein, George, Vakili, Mohammadjavad, Yepes, Gustavo, Institut d'Astrophysique de Paris (IAP), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) |
| المصدر: | Monthly Notices of the RAS (0035-8711), 482(2), 1786-1806 Mon.Not.Roy.Astron.Soc. Mon.Not.Roy.Astron.Soc., 2019, 482 (2), pp.1786-1806. ⟨10.1093/mnras/sty2757⟩ Lippich, M, Sánchez, A G, Colavincenzo, M, Sefusatti, E, Monaco, P, Blot, L, Crocce, M, Alvarez, M A, Agrawal, A, Avila, S, Balaguera-Antolínez, A, Bond, R, Codis, S, Vecchia, C D, Dorta, A, Fosalba, P, Izard, A, Kitaura, F-S, Pellejero-Ibanez, M, Stein, G, Vakili, M & Yepes, G 2019, ' Comparing approximate methods for mock catalogues and covariance matrices I : correlation function ', Monthly Notices of the Royal Astronomical Society, vol. 482, no. 2, pp. 1786-1806 . https://doi.org/10.1093/mnras/sty2757 |
| سنة النشر: | 2018 |
| مصطلحات موضوعية: | Cosmology and Nongalactic Astrophysics (astro-ph.CO), Calibration (statistics), FOS: Physical sciences, Probability density function, Correlation function (astronomy), 01 natural sciences, 0103 physical sciences, cosmological parameters, large-scale structure of Universe, Statistical physics, Cluster analysis, 010303 astronomy & astrophysics, STFC, Physics, Number density, 010308 nuclear & particles physics, RCUK, Astronomy and Astrophysics, Covariance, Amplitude, ST/K00283X/1, Space and Planetary Science, astro-ph.CO, cosmological parameter, Focus (optics), [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Astrophysics - Cosmology and Nongalactic Astrophysics |
| الوصف: | This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic two-point correlation function measurements. Our comparison includes seven approximate methods, which can be divided into three categories: predictive methods that follow the evolution of the linear density field deterministically (ICE-COLA, Peak Patch, and Pinocchio), methods that require a calibration with N-body simulations (Patchy and Halogen), and simpler recipes based on assumptions regarding the shape of the probability distribution function (PDF) of density fluctuations (log-normal and Gaussian density fields). We analyse the impact of using covariance estimates obtained from these approximate methods on cosmological analyses of galaxy clustering measurements, using as a reference the covariances inferred from a set of full N-body simulations. We find that all approximate methods can accurately recover the mean parameter values inferred using the N-body covariances. The obtained parameter uncertainties typically agree with the corresponding N-body results within 5% for our lower mass threshold, and 10% for our higher mass threshold. Furthermore, we find that the constraints for some methods can differ by up to 20% depending on whether the halo samples used to define the covariance matrices are defined by matching the mass, number density, or clustering amplitude of the parent N-body samples. The results of our configuration-space analysis indicate that most approximate methods provide similar results, with no single method clearly outperforming the others. Comment: 23 pages, 11 figures. Replaced to match accepted MNRAS version. Included Kullback-Leibler divergence |
| وصف الملف: | application/pdf |
| اللغة: | English |
| DOI: | 10.1093/mnras/sty2757⟩ |
| DOI: | 10.1093/mnras/sty2757 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6542bf824e4025b86dc263efa3cbb41 http://hdl.handle.net/1887/84665 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....b6542bf824e4025b86dc263efa3cbb41 |
| قاعدة البيانات: | OpenAIRE |
| DOI: | 10.1093/mnras/sty2757⟩ |
|---|