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arXiv · 0911.2454

Simultaneous measurement of cosmology and intrinsic alignments using joint cosmic shear and galaxy number density correlations

Abstract

Cosmic shear is a powerful method to constrain cosmology, provided that any systematic effects are under control. The intrinsic alignment of galaxies is expected to severely bias parameter estimates if not taken into account. We explore the potential of a joint analysis of tomographic galaxy ellipticity, galaxy number density, and ellipticity-number density cross-correlations to simultaneously constrain cosmology and self-calibrate unknown intrinsic alignment and galaxy bias contributions. We treat intrinsic alignments and galaxy biasing as free functions of scale and redshift and marginalise over the resulting parameter sets. Constraints on cosmology are calculated by combining the likelihoods from all two-point correlations between galaxy ellipticity and galaxy number density. The information required for these calculations is already available in a standard cosmic shear dataset. We include contributions to these functions from cosmic shear, intrinsic alignments, galaxy clustering and magnification effects. In a Fisher matrix analysis we compare our constraints with those from cosmic shear alone in the absence of intrinsic alignments. For a potential future large area survey, such as Euclid, the extra information from the additional correlation functions can make up for the additional free parameters in the intrinsic alignment and galaxy bias terms, depending on the flexibility in the models. For example, the Dark Energy Task Force figure of merit is recovered even when more than 100 free parameters are marginalised over. We find that the redshift quality requirements are similar to those calculated in the absence of intrinsic alignments.

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BibTeXRIS

B. Joachimi, S. L. Bridle. 2009-11-12. Simultaneous measurement of cosmology and intrinsic alignments using joint cosmic shear and galaxy number density correlations. https://doi.org/10.1051/0004-6361/200913657

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