Context. This work focuses on the submillimeter galaxy magnification bias, specifically in the tomographic scenario. It builds upon previous works, while utilising updated data to refine the methodology employed in constraining the free parameters of the halo occupation distribution model and cosmological parameters within a flat ΛCDM model.
Aims. This work aims to optimise CPU time and explore strategies for analysing different redshift bins, while maintaining measurement precision. Additionally, it seeks to examine the impact of excluding the GAMA15 field, one of the H-ATLAS fields that was found to have an anomalous strong cross-correlation signal, and increasing the number of redshift bins on the results.
Methods. The study uses a tomographic approach, dividing the redshift range into a different number of bins and analysing cross-correlation measurements between H-ATLAS submillimeter galaxies with photometric redshifts in the range 1.2 < z < 4.0 and foreground GAMA galaxies with spectroscopic redshifts in the range 0.01 < z < 0.9. Interpreting the weak lensing signal within the halo model formalism and carrying out a Markov chain Monte Carlo algorithm, we obtain the posterior distribution of both halo occupation distribution and cosmological parameters within a flat ΛCDM model. Comparative analyses are conducted between different scenarios, including different combinations of redshift bins and the inclusion or exclusion of the GAMA15 field.
Results. The mean-redshift approximation employed in the “base case” yields results that are in good agreement with the more computationally intensive “full model” case. Marginalised posterior distributions confirm a systematic increase in the minimum mass of the lenses with increasing redshift. The inferred cosmological parameters show narrower posterior distributions compared to previous studies on the same topic, indicating reduced measurement uncertainties. Excluding the GAMA15 field demonstrates a reduction in the cross-correlation signal, particularly in two of the redshift bins, suggesting a sample variance within the large-scale structure along the line of sight. Moreover, extending the redshift range improves the robustness against the sample variance issue and produces similar, but tighter constraints compared to excluding the GAMA15 field.
Conclusions. The study emphasises the importance of considering sample variance and redshift binning in tomographic analyses. Increasing the number of independent fields and the number of redshift bins can minimise both the spatial and redshift sample variance, resulting in more robust measurements. The adoption of additional wide area field observed by Herschel and of updated foreground catalogues, such as the Dark Energy Survey or the future Euclid mission, is important for implementing these approaches effectively.