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Beware of commonly used approximations: Part I. Errors in forecasts

In the era of precision cosmology, establishing the correct magnitude of statistical errors in cosmological parameters is of crucial importance. However, widely used approximations in galaxy surveys analyses can lead to parameter uncertainties that are grossly mis-estimated, even in a regime where t...

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Detalles Bibliográficos
Autores principales: Bellomo, Nicola, Bernal, José Luis, Scelfo, Giulio, Raccanelli, Alvise, Verde, Licia
Lenguaje:eng
Publicado: 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1475-7516/2020/10/016
http://cds.cern.ch/record/2723984
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author Bellomo, Nicola
Bernal, José Luis
Scelfo, Giulio
Raccanelli, Alvise
Verde, Licia
author_facet Bellomo, Nicola
Bernal, José Luis
Scelfo, Giulio
Raccanelli, Alvise
Verde, Licia
author_sort Bellomo, Nicola
collection CERN
description In the era of precision cosmology, establishing the correct magnitude of statistical errors in cosmological parameters is of crucial importance. However, widely used approximations in galaxy surveys analyses can lead to parameter uncertainties that are grossly mis-estimated, even in a regime where the theory is well understood (e.g., linear scales). These approximations can be introduced at three different levels: in the form of the likelihood, in the theoretical modelling of the observable and in the numerical computation of the observable. Their consequences are important both in data analysis through e.g., Markov Chain Monte Carlo parameter inference, and when survey instrument and strategy are designed and their constraining power on cosmological parameters is forecasted, for instance using Fisher matrix analyses. In this work, considering the galaxy angular power spectrum as the target observable, we report one example of approximation for each of such three categories: neglecting off-diagonal terms in the covariance matrix, neglecting cosmic magnification and using the Limber approximation on large scales. We show that these commonly used approximations affect the robustness of the analysis and lead, perhaps counter-intuitively, to unacceptably large mis-estimates of parameters errors (from few 10% up to few 100%) and correlations. Furthermore, these approximations might even spoil the benefits of the nascent multi-tracer and multi-messenger cosmology. Hence we recommend that the type of analysis presented here should be repeated for every approximation adopted in survey design or data analysis, to quantify how it may affect the results. To this aim, we have developed Multi_CLASS, a new extension of CLASS that includes the angular power spectrum for multiple (galaxy and other tracers such as gravitational waves) populations. The public release of Multi_CLASS is associated with this paper.
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spelling cern-27239842023-10-04T07:57:07Zdoi:10.1088/1475-7516/2020/10/016http://cds.cern.ch/record/2723984engBellomo, NicolaBernal, José LuisScelfo, GiulioRaccanelli, AlviseVerde, LiciaBeware of commonly used approximations: Part I. Errors in forecastsastro-ph.COAstrophysics and AstronomyIn the era of precision cosmology, establishing the correct magnitude of statistical errors in cosmological parameters is of crucial importance. However, widely used approximations in galaxy surveys analyses can lead to parameter uncertainties that are grossly mis-estimated, even in a regime where the theory is well understood (e.g., linear scales). These approximations can be introduced at three different levels: in the form of the likelihood, in the theoretical modelling of the observable and in the numerical computation of the observable. Their consequences are important both in data analysis through e.g., Markov Chain Monte Carlo parameter inference, and when survey instrument and strategy are designed and their constraining power on cosmological parameters is forecasted, for instance using Fisher matrix analyses. In this work, considering the galaxy angular power spectrum as the target observable, we report one example of approximation for each of such three categories: neglecting off-diagonal terms in the covariance matrix, neglecting cosmic magnification and using the Limber approximation on large scales. We show that these commonly used approximations affect the robustness of the analysis and lead, perhaps counter-intuitively, to unacceptably large mis-estimates of parameters errors (from few 10% up to few 100%) and correlations. Furthermore, these approximations might even spoil the benefits of the nascent multi-tracer and multi-messenger cosmology. Hence we recommend that the type of analysis presented here should be repeated for every approximation adopted in survey design or data analysis, to quantify how it may affect the results. To this aim, we have developed Multi_CLASS, a new extension of CLASS that includes the angular power spectrum for multiple (galaxy and other tracers such as gravitational waves) populations. The public release of Multi_CLASS is associated with this paper.In the era of precision cosmology, establishing the correct magnitude of statistical errors in cosmological parameters is of crucial importance. However, widely used approximations in galaxy surveys analyses can lead to parameter uncertainties that are grossly mis-estimated, even in a regime where the theory is well understood (e.g., linear scales). These approximations can be introduced at three different levels: in the form of the likelihood, in the theoretical modelling of the observable and in the numerical computation of the observable. Their consequences are important both in data analysis through e.g., Markov Chain Monte Carlo parameter inference, and when survey instrument and strategy are designed and their constraining power on cosmological parameters is forecasted, for instance using Fisher matrix analyses. In this work, considering the galaxy angular power spectrum as the target observable, we report one example of approximation for each of such three categories: neglecting off-diagonal terms in the covariance matrix, neglecting cosmic magnification and using the Limber approximation on large scales. We show that these commonly used approximations affect the robustness of the analysis and lead, perhaps counter-intuitively, to unacceptably large mis-estimates of parameters errors (from few~$10\%$ up to few~$100\%$) and correlations. Furthermore, these approximations might even spoil the benefits of the nascent multi-tracer and multi-messenger cosmology. Hence we recommend that the type of analysis presented here should be repeated for every approximation adopted in survey design or data analysis, to quantify how it may affect the results. To this aim, we have developed \texttt{Multi\_CLASS}, a new extension of \texttt{CLASS} that includes the angular power spectrum for multiple (galaxy and other tracers such as gravitational waves) populations.arXiv:2005.10384CERN-TH-2020-044oai:cds.cern.ch:27239842020-05-20
spellingShingle astro-ph.CO
Astrophysics and Astronomy
Bellomo, Nicola
Bernal, José Luis
Scelfo, Giulio
Raccanelli, Alvise
Verde, Licia
Beware of commonly used approximations: Part I. Errors in forecasts
title Beware of commonly used approximations: Part I. Errors in forecasts
title_full Beware of commonly used approximations: Part I. Errors in forecasts
title_fullStr Beware of commonly used approximations: Part I. Errors in forecasts
title_full_unstemmed Beware of commonly used approximations: Part I. Errors in forecasts
title_short Beware of commonly used approximations: Part I. Errors in forecasts
title_sort beware of commonly used approximations: part i. errors in forecasts
topic astro-ph.CO
Astrophysics and Astronomy
url https://dx.doi.org/10.1088/1475-7516/2020/10/016
http://cds.cern.ch/record/2723984
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