KiDS plus GAMA: Cosmology constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing, and angular clustering

Journal article

We present cosmological parameter constraints from a joint analysis of three cosmological probes: the tomographic cosmic shear signal in~450 deg2of data from the Kilo Degree Survey (KiDS), the galaxy-matter cross-correlation signal of galaxies from the Galaxies And Mass Assembly (GAMA) survey determined with KiDS weak lensing, and the angular correlation function of the same GAMA galaxies. We use fast power spectrum estimators that are based on simple integrals over the real-space correlation functions, and show that they are practically unbiased over relevant angular frequency ranges. We test our full pipeline on numerical simulations that are tailored to KiDS and retrieve the input cosmology. By fitting different combinations of power spectra, we demonstrate that the three probes are internally consistent. For all probes combined, we obtain S8≡ σ8√ Ωm/0.3 = 0.800-0.027+0.029, consistent with Planck and the fiducial KiDS-450 cosmic shear correlation function results. Marginalizing over wide priors on the mean of the tomographic redshift distributions yields consistent results for S8with an increase of 28 per cent in the error. The combination of probes results in a 26 per cent reduction in uncertainties of S8over using the cosmic shear power spectra alone. The main gain from these additional probes comes through their constraining power on nuisance parameters, such as the galaxy intrinsic alignment amplitude or potential shifts in the redshift distributions, which are up to a factor of 2 better constrained compared to using cosmic shear alone, demonstrating the value of large-scale structure probe combination.

Authors: Van Uitert, E; Joachimi, B; Joudaki, S; Amon, A; Heymans, C

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Oxford University Press
• Journal: Monthly Notices of the Royal Astronomical Society
• Volume: 476
• Issue: 4
• Pages: 4662-4689
• Publication date: 2018-03-14
• Acceptance date: 2018-02-23
• DOI: 10.1093/mnras/sty551
• EISSN: 1365-2966
• ISSN: 0035-8711
• Keywords: large-scale structure of Universe; methods: data analysis; methods: statistical