Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data
Year: 2018
Type: article
Abstract: Galaxy cross-correlations with high-fidelity redshift samples hold the potential to precisely calibrate systematic photometric redshift uncertainties arising from the unavailability of complete and representative training and validation samples of galaxies. However, application of this technique in the Dark Energy Survey (DES) is hampered by the relatively low number density, small area, and modest redshift overlap between photometric and spectroscopic samples. We propose instead using photometric catalogues with reliable photometric redshifts for photo-z calibration via cross-correlations. We verify the viability of our proposal using redMaPPer clusters from the Sloan Digital Sky Survey (SDSS) to successfully recover the redshift distribution of SDSS spectroscopic galaxies. We demonstrate how to combine photo-z with cross-correlation data to calibrate photometric redshift biases while marginalizing over possible clustering bias evolution in either the calibration or unknown photometric samples. We apply our method to DES Science Verification (DES SV) data in order to constrain the photometric redshift distribution of a galaxy sample selected for weak lensing studies, constraining the mean of the tomographic redshift distributions to a statistical uncertainty of Δz ∼ ±0.01. We forecast that our proposal can, in principle, control photometric redshift uncertainties in DES weak lensing experiments at a level near the intrinsic statistical noise of the experiment over the range of redshifts where redMaPPer clusters are available. Our results provide strong motivation to launch a programme to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.
DOI: 10.1093/mnras/sty787
Authors: C Davis, E Rozo, A Roodman, A Alarcon, R Cawthon, M Gatti, H Lin, R Miquel, E S Rykoff, M A Troxel, P Vielzeuf, T M C Abbott, F B Abdalla, S Allam, J Annis, K Bechtol, A Benoit-Lévy, E Bertin, D Brooks, E Buckley-Geer, D L Burke, A Carnero Rosell, M Carrasco Kind, J Carretero, F J Castander, M Crocce, C E Cunha, C B D'Andrea, L N da Costa, S Desai, H T Diehl, P Doel, A Drlica-Wagner, A Fausti Neto, B Flaugher, P Fosalba, J Frieman, J García-Bellido, E Gaztanaga, D W Gerdes, T Giannantonio, D Gruen, R A Gruendl, G Gutierrez, K Honscheid, B Jain, D J James, T Jeltema, E Krause, K Kuehn, S Kuhlmann, N Kuropatkin, O Lahav, T S Li, M Lima, M March, J L Marshall, P Martini, P Melchior, R L C Ogando, A A Plazas, A K Romer, E Sanchez, V Scarpine, R Schindler, M Schubnell, I Sevilla-Noarbe, M Smith, M Soares-Santos, F Sobreira, E Suchyta, M E C Swanson, G Tarle, D Thomas, V Vikram, A R Walker, R H Wechsler
Institutions: Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, University of Arizona, SLAC National Accelerator Laboratory, Institute of Space Sciences, University of Chicago, Institute for High Energy Physics, Barcelona Institute of Science and Technology, Fermi National Accelerator Laboratory, Institució Catalana de Recerca i Estudis Avançats, The Ohio State University, Cerro Tololo Inter-American Observatory, Rhodes University, University College London, Large Synoptic Survey Telescope Corporation, Centre National de la Recherche Scientifique, Institut d'Astrophysique de Paris, Université Pierre-et-Marie-Curie, National Observatory, Laboratório Interinstitucional de e-Astronomia, University of Illinois Urbana-Champaign, National Center for Supercomputing Applications, University of Pennsylvania, Indian Institute of Technology Hyderabad, Instituto de Física Teórica, Universidad Autónoma de Madrid, University of Michigan, University of Cambridge, Ludwig-Maximilians-Universität München, University of Washington, University of California, Santa Cruz, Australian Astronomical Observatory, Argonne National Laboratory, Universidade de São Paulo, Texas A&M University, Princeton University, Jet Propulsion Laboratory, University of Sussex, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, University of Southampton, Universidade Estadual de Campinas (UNICAMP), Oak Ridge National Laboratory, University of Portsmouth
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
Funders: National Science Foundation, U.S. Department of Energy, Alfred P. Sloan Foundation, University of Pennsylvania, Ohio State University, University of Chicago, University of Michigan, Achievement Rewards for College Scientists Foundation, University of Portsmouth, Centres de Recerca de Catalunya, University of Cambridge, University College London, European Commission, University of Nottingham, University of Sussex, University of Edinburgh, Deutsche Forschungsgemeinschaft, Generalitat de Catalunya, Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Financiadora de Estudos e Projetos, Institut de Física d'Altes Energies, University of Illinois at Urbana-Champaign, Science and Technology Facilities Council, European Regional Development Fund, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Integrated Electronics Engineering Center, Binghamton University, Argonne National Laboratory, Fermilab, Lawrence Berkeley National Laboratory, SLAC National Accelerator Laboratory
Awards: G1313983767, G1491530973, G1750188476, G1794164356, G2409381996, G303061748, Additional AGP funding - supplementary to Sussex Consolidated Grant ST/L000652/1, The Dark Energy Survey Data Management Operations, University of Sussex Astronomy Consolidated Grant 2017-2020, CONSTRAINING DARK ENERGY WITH GALAXY CLUSTERS AND BARYON ACOUSTIC OSCILLATIONS, G4559126160, G4817264520, G5211491313, G6889587812, G7038324121, G7088042312, G7290792616, The Dark Energy Survey: Education and Public Outreach, G7788408655, G7835623888, Collaborative Research: The Dark Energy Survey Data Management Operations, G969889393
OpenAlex ID: W2738047492