http://arxiv.org/abs/1909.09632
Accurate photometric redshift calibration is central to the robustness of all cosmology constraints from cosmic shear surveys. Analyses of the Kilo-Degree Survey, KiDS, re-weighted training samples from all overlapping spectroscopic surveys to provide a direct redshift calibration. Using self-organising maps (SOMs) we demonstrate that this spectroscopic compilation is sufficiently complete for KiDS, representing $99\%$ of the effective 2D cosmic shear sample. We use the SOM to define a $100\%$ represented
gold' cosmic shear sample, per tomographic bin. Using mock simulations of KiDS and the spectroscopic training set, we demonstrate that the mean redshift of thegold’ sample can be recovered by the SOM with an accuracy better than $| \Delta \langle z \rangle | < 0.004$, with the exception of the $0.7 < z_B < 0.9$ tomographic bin with $ |\Delta \langle z \rangle | = 0.011$. Photometric noise, sample variance, and spectroscopic selection effects induce a combined maximal scatter of $\sigma_{\Delta \langle z \rangle} < 0.007$ in all tomographic bins. We demonstrate that the previous direct redshift calibration method applied to the full cosmic shear sample is accurate to $| \Delta \langle z \rangle | < 0.025$. We find that photometric noise dominates the calibration dispersion, and that neither sampling variance nor a realistic fraction of spectroscopic misidentifications in the training set introduce significant bias.
A. Wright, H. Hildebrandt, J. Busch, et. al.
Mon, 23 Sep 19
7/46
Comments: 26 pages, 14 figures, 6 appendices, submitted to A&A