Abstract
Aims. The main goal of this work is to test the results of a methodological improvement in the measurement of the magnification bias signal on a sample of submillimeter galaxies. In particular, we investigate the constraining power of cosmological parameters within the ΛCDM model. We also discuss important points that can affect the results.
Methods. We measured the angular cross-correlation function between a sample of foreground GAMA II galaxies in a single wide spectroscopic redshift bin of 0.2 < z < 0.8 and a sample of background submillimeter galaxies from Herschel-ATLAS. We focused on the photometric redshift range of 1.2 < z < 4.0, with an improved methodological framework. Interpreting the weak lensing signal within the halo model formalism and performing a Markov chain Monte Carlo (MCMC) algorithm, we obtained the posterior distribution of both the halo occupation distribution and cosmological parameters within a flat ΛCDM model. Our analysis was also performed with additional galaxy clustering information via a foreground angular auto-correlation function.
Results. We observed an overall remarkable improvement in terms of uncertainties in both the halo occupation distribution and cosmological parameters with respect to previous results. A priori knowledge about β, the logarithmic slope of the background integral number counts, is found to be paramount to derive constraints on σ8 when using the cross-correlation data alone. Assuming a physically motivated prior distribution for β, we obtain mean values of Ωm = 0.23−0.06+0.03 and σ8 = 0.79−0.10+0.10 and an unconstrained distribution for the Hubble constant. These results are likely to suffer from sampling variance, since one of the fields, G15, appears to have an anomalous behavior with a systematically higher cross-correlation. We find that removing it from the sample yields mean values of Ωm = 0.27−0.04+0.02 and σ8 = 0.72−0.04+0.04 and, for the first time, a (loose) restriction of the Hubble constant is obtained via this observable: h = 0.79−0.14+0.13. The addition of the angular auto-correlation of the foreground sample in a joint analysis tightens the constraints, but also reveals a discrepancy between both observables that might be an aggravated consequence of sampling variance or due to the presence of unmodeled aspects on small and intermediate scales.
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