ABSTRACT
When analysing galaxy clustering in multiband imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision, which generally includes only a small subset of galaxies. In this paper, we systematically explore this trade-off. Our analysis is targeted towards the third-year data of the Dark Energy Survey (DES), but our methods hold generally for other data sets. Using a simple Gaussian model for the redshift uncertainties, we carry out a Fisher matrix forecast for cosmological constraints from angular clustering in the redshift range z = 0.2–0.95. We quantify the cosmological constraints using a figure of merit (FoM) that measures the combined constraints on Ωm and σ8 in the context of Λ cold dark matter (ΛCDM) cosmology. We find that the trade-off between sample size and photo-z precision is sensitive to (1) whether cross-correlations between redshift bins are included or not, and (2) the ratio of the redshift bin width δz to the photo-z precision σz. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when δz ∼ σz. We find that for the typical case of 5−10 redshift bins, optimal results are reached when we use larger, less precise photo-z samples, provided that we include cross-correlations. For samples with higher σz, the overlap between redshift bins is larger, leading to higher cross-correlation amplitudes. This leads to the self-calibration of the photo-z parameters and therefore tighter cosmological constraints. These results can be used to help guide galaxy sample selection for clustering analysis in ongoing and future photometric surveys.
USING CROSS CORRELATIONS TO CALIBRATE LENSING SOURCE REDSHIFT DISTRIBUTIONS: IMPROVING COSMOLOGICAL CONSTRAINTS FROM UPCOMING WEAK LENSING SURVEYS
