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dc.contributor.authorCamera, Stefano
dc.contributor.authorTanidis, Konstantinos
dc.contributor.authorParkinson, David
dc.date.accessioned2021-02-12T10:34:29Z
dc.date.available2021-02-12T10:34:29Z
dc.date.issued2019
dc.identifier.citationCamera, S. et al. (2020). Developing a unified pipeline for large-scale structure data analysis with angular power spectra – II. A case study for magnification bias and radio continuum surveys. Monthly Notices of the Royal Astronomical Society,491(4), 4869–4883en_US
dc.identifier.issn1365-2966
dc.identifier.urihttps://doi.org/10.1093/mnras/stz3394
dc.identifier.urihttp://hdl.handle.net/10566/5913
dc.description.abstractFollowing on our purpose of developing a unified pipeline for large-scale structure data analysis with angular power spectra, we now include the weak lensing effect of magnification bias on galaxy clustering in a publicly available, modular parameter estimation code. We thus forecast constraints on the parameters of the concordance cosmological model, dark energy, and modified gravity theories from galaxy clustering tomographic angular power spectra. We find that a correct modelling of magnification is crucial not to bias the parameter estimation, especially in the case of deep galaxy surveys. Our case study adopts specifications of the Evolutionary Map of the Universe, which is a full-sky, deep radio-continuum survey, expected to probe the Universe up to redshift z ∼ 6. We assume the Limber approximation, and include magnification bias on top of density fluctuations and redshift-space distortions. By restricting our analysis to the regime where the Limber approximation holds true, we significantly minimize the computational time needed, compared to that of the exact calculation.en_US
dc.language.isoenen_US
dc.publisherOxford University Pressen_US
dc.subjectCosmological parametersen_US
dc.subjectCosmology: observationsen_US
dc.subjectCosmology: theoryen_US
dc.subjectLarge-scale structure of Universeen_US
dc.subjectRadio continuum surveysen_US
dc.titleDeveloping a unified pipeline for large-scale structure data analysis with angular power spectra – II. A case study for magnification bias and radio continuum surveysen_US
dc.typeArticleen_US


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