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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...
Autores principales: | , , , |
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Lenguaje: | eng |
Publicado: |
2020
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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. |
id | cern-2729995 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
record_format | invenio |
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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