Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
DOI: | 10.1093/mnras/stab2384 |
Texto Completo: | http://dx.doi.org/10.1093/mnras/stab2384 http://hdl.handle.net/11449/229920 |
Resumo: | We describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot noise, galaxy weighting schemes, and other sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness of fit and parameter estimation. The largest impact on best-fitting figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the χ2 between maximum posterior model and measurement by $3.7{{\ \rm per\ cent} (Δχ2 ≈ 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for ωm and σ8 by about $3{{\ \rm per\ cent} and for the dark energy equation-of-state parameter by about $5{{\ \rm per\ cent}. |
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Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fitcosmology: observationslarge-scale structure of UniverseWe describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot noise, galaxy weighting schemes, and other sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness of fit and parameter estimation. The largest impact on best-fitting figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the χ2 between maximum posterior model and measurement by $3.7{{\ \rm per\ cent} (Δχ2 ≈ 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for ωm and σ8 by about $3{{\ \rm per\ cent} and for the dark energy equation-of-state parameter by about $5{{\ \rm per\ cent}.Kavli Institute for Cosmology University of Cambridge, Madingley RoadChurchill College University of CambridgeInstituto de Física Teórica Universidade Estadual PaulistaLaboratório Interinstitucional de e-Astronomia - LIneA, Rua Gal. José Cristino 77Department of Physics University of MichiganICTP South American Institute for Fundamental Research Instituto de Física Teórica Universidade Estadual PaulistaFermi National Accelerator Laboratory, PO Box 500Department of Astronomy/Steward Observatory University of Arizona, 933 North Cherry AvenueJet Propulsion Laboratory California Institute of Technology, 4800 Oak Grove DriveDepartment of Astronomy and Astrophysics University of ChicagoKavli Institute for Cosmological Physics University of ChicagoKavli Institute for Particle Astrophysics and Cosmology Stanford University, PO Box 2450Department of Physics and Astronomy University of Hawaii, Watanabe 416, 2505 Correa RoadCenter for Cosmology and Astro-Particle Physics Ohio State UniversityDepartment of Physics Ohio State UniversityInstitut d'Estudis Espacials de Catalunya (IEEC)Institute of Space Sciences ICE CSIC Campus UAB, Carrer de Can Magrans, s/nSLAC National Accelerator LaboratoryNational Center for Supercomputing Applications, 1205 West Clark StreetDepartment of Physics Stanford University, 382 Via Pueblo MallCentro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT)Institute of Cosmology and Gravitation University of PortsmouthDepartment of Physics and Astronomy Pevensey Building University of SussexInstitute of Astronomy University of Cambridge, Madingley RoadDepartment of Astrophysical Sciences Princeton University, Peyton HallSchool of Physics and Astronomy University of SouthamptonComputer Science and Mathematics Division Oak Ridge National LaboratoryMax Planck Institute for Extraterrestrial Physics, GiessenbachstrasseUniversitäts-Sternwarte Fakultät für Physik Ludwig-Maximilians Universität München, Scheinerstr 1Instituto de Física Teórica Universidade Estadual PaulistaICTP South American Institute for Fundamental Research Instituto de Física Teórica Universidade Estadual PaulistaUniversity of CambridgeUniversidade Estadual Paulista (UNESP)Laboratório Interinstitucional de e-Astronomia - LIneAUniversity of MichiganFermi National Accelerator LaboratoryUniversity of ArizonaCalifornia Institute of TechnologyUniversity of ChicagoStanford UniversityUniversity of HawaiiOhio State UniversityInstitut d'Estudis Espacials de Catalunya (IEEC)CSICSLAC National Accelerator LaboratoryNational Center for Supercomputing ApplicationsMedioambientales y Tecnológicas (CIEMAT)University of PortsmouthUniversity of SussexPrinceton UniversityUniversity of SouthamptonOak Ridge National LaboratoryMax Planck Institute for Extraterrestrial PhysicsLudwig-Maximilians Universität MünchenFriedrich, O.Andrade-Oliveira, F. [UNESP]Camacho, H. [UNESP]Alves, O. [UNESP]Rosenfeld, R. [UNESP]Sanchez, J.Fang, X.Eifler, T. F.Krause, E.Chang, C.Omori, Y.Amon, A.Baxter, E.Elvin-Poole, J.Huterer, D.Palmese, A.Paz-Chinchon, F.Plazas, A. A.Sanchez, E.Scarpine, V.Serrano, S.Soares-Santos, M.Smith, M.Suchyta, E.Tarle, G.Thomas, D.Too, C.Varga, T. N.Weller, J.Wilkinson, R. D.2022-04-29T08:36:40Z2022-04-29T08:36:40Z2021-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article3125-3165http://dx.doi.org/10.1093/mnras/stab2384Monthly Notices of the Royal Astronomical Society, v. 508, n. 3, p. 3125-3165, 2021.1365-29660035-8711http://hdl.handle.net/11449/22992010.1093/mnras/stab23842-s2.0-85119534052Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMonthly Notices of the Royal Astronomical Societyinfo:eu-repo/semantics/openAccess2022-04-29T08:36:40Zoai:repositorio.unesp.br:11449/229920Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:31:32.671101Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit |
title |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit |
spellingShingle |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit Friedrich, O. cosmology: observations large-scale structure of Universe Friedrich, O. cosmology: observations large-scale structure of Universe |
title_short |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit |
title_full |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit |
title_fullStr |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit |
title_full_unstemmed |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit |
title_sort |
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit |
author |
Friedrich, O. |
author_facet |
Friedrich, O. Friedrich, O. Andrade-Oliveira, F. [UNESP] Camacho, H. [UNESP] Alves, O. [UNESP] Rosenfeld, R. [UNESP] Sanchez, J. Fang, X. Eifler, T. F. Krause, E. Chang, C. Omori, Y. Amon, A. Baxter, E. Elvin-Poole, J. Huterer, D. Palmese, A. Paz-Chinchon, F. Plazas, A. A. Sanchez, E. Scarpine, V. Serrano, S. Soares-Santos, M. Smith, M. Suchyta, E. Tarle, G. Thomas, D. Too, C. Varga, T. N. Weller, J. Wilkinson, R. D. Andrade-Oliveira, F. [UNESP] Camacho, H. [UNESP] Alves, O. [UNESP] Rosenfeld, R. [UNESP] Sanchez, J. Fang, X. Eifler, T. F. Krause, E. Chang, C. Omori, Y. Amon, A. Baxter, E. Elvin-Poole, J. Huterer, D. Palmese, A. Paz-Chinchon, F. Plazas, A. A. Sanchez, E. Scarpine, V. Serrano, S. Soares-Santos, M. Smith, M. Suchyta, E. Tarle, G. Thomas, D. Too, C. Varga, T. N. Weller, J. Wilkinson, R. D. |
author_role |
author |
author2 |
Andrade-Oliveira, F. [UNESP] Camacho, H. [UNESP] Alves, O. [UNESP] Rosenfeld, R. [UNESP] Sanchez, J. Fang, X. Eifler, T. F. Krause, E. Chang, C. Omori, Y. Amon, A. Baxter, E. Elvin-Poole, J. Huterer, D. Palmese, A. Paz-Chinchon, F. Plazas, A. A. Sanchez, E. Scarpine, V. Serrano, S. Soares-Santos, M. Smith, M. Suchyta, E. Tarle, G. Thomas, D. Too, C. Varga, T. N. Weller, J. Wilkinson, R. D. |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
University of Cambridge Universidade Estadual Paulista (UNESP) Laboratório Interinstitucional de e-Astronomia - LIneA University of Michigan Fermi National Accelerator Laboratory University of Arizona California Institute of Technology University of Chicago Stanford University University of Hawaii Ohio State University Institut d'Estudis Espacials de Catalunya (IEEC) CSIC SLAC National Accelerator Laboratory National Center for Supercomputing Applications Medioambientales y Tecnológicas (CIEMAT) University of Portsmouth University of Sussex Princeton University University of Southampton Oak Ridge National Laboratory Max Planck Institute for Extraterrestrial Physics Ludwig-Maximilians Universität München |
dc.contributor.author.fl_str_mv |
Friedrich, O. Andrade-Oliveira, F. [UNESP] Camacho, H. [UNESP] Alves, O. [UNESP] Rosenfeld, R. [UNESP] Sanchez, J. Fang, X. Eifler, T. F. Krause, E. Chang, C. Omori, Y. Amon, A. Baxter, E. Elvin-Poole, J. Huterer, D. Palmese, A. Paz-Chinchon, F. Plazas, A. A. Sanchez, E. Scarpine, V. Serrano, S. Soares-Santos, M. Smith, M. Suchyta, E. Tarle, G. Thomas, D. Too, C. Varga, T. N. Weller, J. Wilkinson, R. D. |
dc.subject.por.fl_str_mv |
cosmology: observations large-scale structure of Universe |
topic |
cosmology: observations large-scale structure of Universe |
description |
We describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot noise, galaxy weighting schemes, and other sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness of fit and parameter estimation. The largest impact on best-fitting figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the χ2 between maximum posterior model and measurement by $3.7{{\ \rm per\ cent} (Δχ2 ≈ 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for ωm and σ8 by about $3{{\ \rm per\ cent} and for the dark energy equation-of-state parameter by about $5{{\ \rm per\ cent}. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-01 2022-04-29T08:36:40Z 2022-04-29T08:36:40Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1093/mnras/stab2384 Monthly Notices of the Royal Astronomical Society, v. 508, n. 3, p. 3125-3165, 2021. 1365-2966 0035-8711 http://hdl.handle.net/11449/229920 10.1093/mnras/stab2384 2-s2.0-85119534052 |
url |
http://dx.doi.org/10.1093/mnras/stab2384 http://hdl.handle.net/11449/229920 |
identifier_str_mv |
Monthly Notices of the Royal Astronomical Society, v. 508, n. 3, p. 3125-3165, 2021. 1365-2966 0035-8711 10.1093/mnras/stab2384 2-s2.0-85119534052 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Monthly Notices of the Royal Astronomical Society |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
3125-3165 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1822182306715009024 |
dc.identifier.doi.none.fl_str_mv |
10.1093/mnras/stab2384 |