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Beware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parameters

Cosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or approximations that were sufficiently accurate so far, may introd...

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Detalles Bibliográficos
Autores principales: Bernal, José Luis, Bellomo, Nicola, Raccanelli, Alvise, Verde, Licia
Lenguaje:eng
Publicado: 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1475-7516/2020/10/017
http://cds.cern.ch/record/2729995
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author Bernal, José Luis
Bellomo, Nicola
Raccanelli, Alvise
Verde, Licia
author_facet Bernal, José Luis
Bellomo, Nicola
Raccanelli, Alvise
Verde, Licia
author_sort Bernal, José Luis
collection CERN
description Cosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or approximations that were sufficiently accurate so far, may introduce significant systematic biases in the parameter best-fit values and jeopardize the robustness of cosmological analyses. We generalize previously proposed expressions to estimate a priori the systematic error introduced in parameter inference due to the use of insufficiently good approximations in the computation of the observable of interest or the assumption of an incorrect underlying model. Although this methodology can be applied to measurements of any scientific field, we illustrate its power by studying the effect of modeling the angular galaxy power spectrum incorrectly. We also introduce Multi_CLASS, a new, public modification of the Boltzmann code CLASS, which includes the possibility to compute angular cross-power spectra for two different tracers. We find that significant biases in most of the cosmological parameters are introduced if one assumes the Limber approximation or neglects lensing magnification in modern galaxy survey analyses, and the effect is in general larger for the multi-tracer case, especially for the parameter controlling primordial non-Gaussianity of the local type, fNL.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2020
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spelling cern-27299952023-10-04T08:52:22Zdoi:10.1088/1475-7516/2020/10/017http://cds.cern.ch/record/2729995engBernal, José LuisBellomo, NicolaRaccanelli, AlviseVerde, LiciaBeware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parametersastro-ph.COAstrophysics and AstronomyCosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or approximations that were sufficiently accurate so far, may introduce significant systematic biases in the parameter best-fit values and jeopardize the robustness of cosmological analyses. We generalize previously proposed expressions to estimate a priori the systematic error introduced in parameter inference due to the use of insufficiently good approximations in the computation of the observable of interest or the assumption of an incorrect underlying model. Although this methodology can be applied to measurements of any scientific field, we illustrate its power by studying the effect of modeling the angular galaxy power spectrum incorrectly. We also introduce Multi_CLASS, a new, public modification of the Boltzmann code CLASS, which includes the possibility to compute angular cross-power spectra for two different tracers. We find that significant biases in most of the cosmological parameters are introduced if one assumes the Limber approximation or neglects lensing magnification in modern galaxy survey analyses, and the effect is in general larger for the multi-tracer case, especially for the parameter controlling primordial non-Gaussianity of the local type, fNL.Cosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or approximations that were sufficiently accurate so far, may introduce significant systematic biases in the parameter best-fit values and jeopardize the robustness of cosmological analyses. We present a general expression to estimate a priori the systematic error introduced in parameter inference due to the use of insufficiently good approximations in the computation of the observable of interest or the assumption of an incorrect underlying model. Although this methodology can be applied to measurements of any scientific field, we illustrate its power by studying the effect of modeling the angular galaxy power spectrum incorrectly. We also introduce Multi_CLASS, a new, public modification of the Boltzmann code CLASS, which includes the possibility to compute angular cross-power spectra for two different tracers. We find that significant biases in most of the cosmological parameters are introduced if one assumes the Limber approximation or neglects lensing magnification in modern galaxy survey analyses, and the effect is in general larger for the multi-tracer case, especially for the parameter controlling primordial non-Gaussianity of the local type, $f_{\rm NL}$.arXiv:2005.09666CERN-TH-2020-054oai:cds.cern.ch:27299952020-05-19
spellingShingle astro-ph.CO
Astrophysics and Astronomy
Bernal, José Luis
Bellomo, Nicola
Raccanelli, Alvise
Verde, Licia
Beware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parameters
title Beware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parameters
title_full Beware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parameters
title_fullStr Beware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parameters
title_full_unstemmed Beware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parameters
title_short Beware of commonly used approximations: Part II. Estimating systematic biases in the best-fit parameters
title_sort beware of commonly used approximations: part ii. estimating systematic biases in the best-fit parameters
topic astro-ph.CO
Astrophysics and Astronomy
url https://dx.doi.org/10.1088/1475-7516/2020/10/017
http://cds.cern.ch/record/2729995
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