MAPPING THE GALAXY COLOR–REDSHIFT RELATION: OPTIMAL PHOTOMETRIC REDSHIFT CALIBRATION STRATEGIES FOR COSMOLOGY SURVEYS

Abstract

Calibrating the photometric redshifts of >10^9 galaxies for upcoming weak\nlensing cosmology experiments is a major challenge for the astrophysics\ncommunity. The path to obtaining the required spectroscopic redshifts for\ntraining and calibration is daunting, given the anticipated depths of the\nsurveys and the difficulty in obtaining secure redshifts for some faint galaxy\npopulations. Here we present an analysis of the problem based on the\nself-organizing map, a method of mapping the distribution of data in a\nhigh-dimensional space and projecting it onto a lower-dimensional\nrepresentation. We apply this method to existing photometric data from the\nCOSMOS survey selected to approximate the anticipated Euclid weak lensing\nsample, enabling us to robustly map the empirical distribution of galaxies in\nthe multidimensional color space defined by the expected Euclid filters.\nMapping this multicolor distribution lets us determine where - in galaxy color\nspace - redshifts from current spectroscopic surveys exist and where they are\nsystematically missing. Crucially, the method lets us determine whether a\nspectroscopic training sample is representative of the full photometric space\noccupied by the galaxies in a survey. We explore optimal sampling techniques\nand estimate the additional spectroscopy needed to map out the color-redshift\nrelation, finding that sampling the galaxy distribution in color space in a\nsystematic way can efficiently meet the calibration requirements. While the\nanalysis presented here focuses on the Euclid survey, similar analysis can be\napplied to other surveys facing the same calibration challenge, such as DES,\nLSST, and WFIRST.\n