On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix

ArXiv ePrint: 2306.03137

Detalles Bibliográficos
Autores: Novell-Masot, Sergi, Gil-Marín, Héctor, Verde, Licia
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/371301
Acceso en línea:http://hdl.handle.net/10261/371301
Access Level:acceso abierto
Palabra clave:Cosmological parameters from LSS
Power spectrum
Statistical sampling techniques
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spelling On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrixNovell-Masot, SergiGil-Marín, HéctorVerde, LiciaCosmological parameters from LSSPower spectrumStatistical sampling techniquesArXiv ePrint: 2306.03137We investigate, in dark matter and galaxy mocks, the effects of approximating the galaxy power spectrum-bispectrum estimated covariance as a diagonal matrix, for an analysis that aligns with the specifications of recent and upcoming galaxy surveys. We find that, for a joint power spectrum and bispectrum data-vector, with corresponding k-ranges of 0.02 < k[hMpc-1] < 0.15 and 0.02 < k[hMpc-1] < 0.12 each, the diagonal covariance approximation recovers ∼ 10% larger error-bars on the parameters {σ8,f,α∥,α⊥} with respect to the full covariance case, while still underestimating the corresponding true errors on the recovered parameters by ∼ 10%. This is caused by the diagonal approximations weighting the elements of the data-vector in a sub-optimal way, resulting in a less efficient estimator, with poor coverage properties, than the maximum likelihood estimator featuring the full covariance matrix. We further investigate intermediate approximations to the full covariance matrix, with up to ∼ 80% of the matrix elements being zero, which could be advantageous for theoretical and hybrid approaches. We expect these results to be qualitatively insensitive to variations of the total cosmological volume, depending primarily on the bin size and shot-noise, thus making them particularly significant for present and future galaxy surveys.SNM acknowledges funding from the official doctoral program of the University of Barcelona for the development of a research project under the PREDOCS-UB grant. HGM acknowledges support through the program Ramón y Cajal (RYC-2021-034104) of the Spanish Ministry of Science and Innovation. LV and HGM acknowledge the support of the European Union’s Horizon 2020 research and innovation program ERC (BePreSySe, grant agreement 725327). Funding for this work was partially provided by the Spanish MINECO under project PGC2018-098866-B-I00MCIN/AEI/10.13039/501100011033 y FEDER “Una manera de hacer Europa”, and the “Center of Excellence Maria de Maeztu 2020–2023” award to the ICCUB (CEX2019-000918-M funded by MCIN/AEI/10.13039/501100011033).With funding from the Spanish government through the "Unit of Excellence Maria de Maeztu" accreditation (CEX2019-000918-M).Peer reviewedIOP PublishingUniversidad de BarcelonaAgencia Estatal de Investigación (España)Ministerio de Ciencia, Innovación y Universidades (España)European CommissionEuropean Research Council202420242024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/371301reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI//RYC-2021-034104info:eu-repo/grantAgreement/EC/H2020/725327info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-098866-B-I00info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/CEX2019-000918-Mhttps://doi.org/10.1088/1475-7516/2024/06/048Noinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3713012026-05-22T06:33:51Z
dc.title.none.fl_str_mv On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
title On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
spellingShingle On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
Novell-Masot, Sergi
Cosmological parameters from LSS
Power spectrum
Statistical sampling techniques
title_short On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
title_full On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
title_fullStr On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
title_full_unstemmed On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
title_sort On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix
dc.creator.none.fl_str_mv Novell-Masot, Sergi
Gil-Marín, Héctor
Verde, Licia
author Novell-Masot, Sergi
author_facet Novell-Masot, Sergi
Gil-Marín, Héctor
Verde, Licia
author_role author
author2 Gil-Marín, Héctor
Verde, Licia
author2_role author
author
dc.contributor.none.fl_str_mv Universidad de Barcelona
Agencia Estatal de Investigación (España)
Ministerio de Ciencia, Innovación y Universidades (España)
European Commission
European Research Council
dc.subject.none.fl_str_mv Cosmological parameters from LSS
Power spectrum
Statistical sampling techniques
topic Cosmological parameters from LSS
Power spectrum
Statistical sampling techniques
description ArXiv ePrint: 2306.03137
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/371301
url http://hdl.handle.net/10261/371301
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
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info:eu-repo/grantAgreement/AEI//RYC-2021-034104
info:eu-repo/grantAgreement/EC/H2020/725327
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-098866-B-I00
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/CEX2019-000918-M
https://doi.org/10.1088/1475-7516/2024/06/048
No
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
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