While the analysis presented here focuses on the Euclid survey, similar analysis can be applied to other surveys facing the same calibration challenge, such as DES, LSST, and WFIRST. We explore optimal sampling techniques and estimate the additional spectroscopy needed to map out the color–redshift relation, finding that sampling the galaxy distribution in color space in a systematic way can efficiently meet the calibration requirements. Crucially, the method lets us determine whether a spectroscopic training sample is representative of the full photometric space occupied by the galaxies in a survey. Mapping this multicolor distribution lets us determine where-in galaxy color space-redshifts from current spectroscopic surveys exist and where they are systematically missing. We apply this method to existing photometric data from the COSMOS survey selected to approximate the anticipated Euclid weak lensing sample, enabling us to robustly map the empirical distribution of galaxies in the multidimensional color space defined by the expected Euclid filters. Here we present an analysis of the problem based on the self-organizing map, a method of mapping the distribution of data in a high-dimensional space and projecting it onto a lower-dimensional representation. The path to obtaining the required spectroscopic redshifts for training and calibration is daunting, given the anticipated depths of the surveys and the difficulty in obtaining secure redshifts for some faint galaxy populations. Massachusetts Institute of Technology, Cambridge, MA 02139, USAĭepartment of Physics and Astronomy, University of Missouri, Kansas City, MO 64110, USAĪstronomical Observatory of Capodimonte-INAF, via Moiariello 16, I-80131, Napoli, ItalyĬalibrating the photometric redshifts of ≳10 9 galaxies for upcoming weak lensing cosmology experiments is a major challenge for the astrophysics community. Box 9513, 2300 RA, Leiden, The NetherlandsĪrgelander-Institut für Astronomie, Universität Bonn, Auf dem H'´ugel 71, D-53121 Bonn, Germanyĭepartment of Astronomy, Harvard University, 60 Garden Street, MS 46, Cambridge, MA 02138, USA Leiden Observatory, Leiden University, P.O. dcogia 16, CH-1290 Versoix, Switzerlandĭepartment of Physics and Astronomy, University of California, Riverside, CA 92521, USA Kavli Institute for the Physics and Mathematics of the Universe, The University of Tokyo, Chiba 277-8582, Japanĭepartment of Astronomy, University of Geneva ch. Max-Planck-Institut für extraterrestrische Physik, Giessenbachstrasse, D-85748 Garching, Germanyĭepartment of Physics, University of California, Davis, CA 95616, USAĭepartment of Physics, University Federico II, via Cinthia 6, I-80126 Napoli, Italy Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USAĪix Marseille Universite, CNRS, LAM (Laboratoire dAstrophysique de Marseille) UMR 7326, F-13388, Marseille, France Spitzer Science Center, California Institute of Technology, Pasadena, CA 91125, USA Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, CA 91125, USA
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |