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arXiv · 1306.6870

On the complementarity of galaxy clustering with cosmic shear and flux magnification

Abstract

In this paper, we motivate the use of galaxy clustering measurements using photometric redshift information, including a contribution from flux magnification, as a probe of cosmology. We present cosmological forecasts when clustering data alone is used, and when clustering is combined with a cosmic shear analysis. We consider two types of clustering analysis: firstly, clustering with only redshift auto-correlations in tomographic redshift bins; secondly, using all available redshift bin correlations. Finally, we consider how inferred cosmological parameters may be biased using each analysis when flux magnification is neglected. Results are presented for a Stage III ground-based survey, and a Stage IV space-based survey modelled with photometric redshift errors, and values for the slope of the luminosity function inferred from CFHTLenS catalogues. We find that combining clustering information with shear can improve constraints on cosmological parameters, giving an improvement to a Dark Energy Task Force-like figure of merit by a factor of 1.33 when only auto-correlations in redshift are used for the clustering analysis, rising to 1.52 when cross-correlations in redshift are also included. The addition of galaxy-galaxy lensing gives further improvement, with increases in figure of merit by a factor of 2.82 and 3.7 for each type of clustering analysis respectively. The presence of flux magnification in a clustering analysis does not significantly affect the precision of cosmological constraints when combined with cosmic shear and galaxy-galaxy lensing. However if magnification is neglected, inferred cosmological parameter values are biased, with biases in some cosmological parameters larger than statistical errors. (Abridged)

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Christopher Duncan, Benjamin Joachimi, Alan Heavens, Catherine Heymans, Hendrik Hildebrandt. 2013-11-15. On the complementarity of galaxy clustering with cosmic shear and flux magnification. https://doi.org/10.1093/mnras%2Fstt2060

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