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Parameter constraints from weak-lensing tomography of galaxy shapes and cosmic microwave background fluctuations

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Recently, it has been shown that cross-correlating cosmic microwave background (CMB) lensing and three-dimensional (3D) cosmic shear allows to considerably tighten cosmological parameter constraints. We investigate whether similar improvement can be achieved in a conventional tomographic setup. We p...

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Bibliographic Details
Main Authors: Merkel, Philipp M. (Author) , Schäfer, Björn Malte (Author)
Format: Article (Journal)
Language:English
Published: 01 May 2017
In: Monthly notices of the Royal Astronomical Society
Year: 2017, Volume: 469, Issue: 3, Pages: 2760-2770
ISSN:1365-2966
DOI:10.1093/mnras/stx1044
Online Access:Verlag, kostenfrei, Volltext: http://dx.doi.org/10.1093/mnras/stx1044
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Author Notes:Philipp M. Merkel and Björn Malte Schäfer
Description
Summary:Recently, it has been shown that cross-correlating cosmic microwave background (CMB) lensing and three-dimensional (3D) cosmic shear allows to considerably tighten cosmological parameter constraints. We investigate whether similar improvement can be achieved in a conventional tomographic setup. We present Fisher parameter forecasts for a Euclid-like galaxy survey in combination with different ongoing and forthcoming CMB experiments. In contrast to a fully 3D analysis, we find only marginal improvement. Assuming Planck-like CMB data, we show that including the full covariance of the combined CMB and cosmic shear data improves the dark energy figure of merit (FOM) by only 3 per cent. The marginalized error on the sum of neutrino masses is reduced at the same level. For a next generation CMB satellite mission such as Prism, the predicted improvement of the dark energy FOM amounts to approximately 25 per cent. Furthermore, we show that the small improvement is contrasted by an increased bias in the dark energy parameters when the intrinsic alignment of galaxies is not correctly accounted for in the full covariance matrix.
Item Description:Gesehen am 19.10.2017
Physical Description:Online Resource
ISSN:1365-2966
DOI:10.1093/mnras/stx1044

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