Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data
Author
Davis, CRozo, E
Roodman, A
Alarcon, A
Cawthon, R
Gatti, M
Lin, H
Miquel, R
Rykoff, E S
Troxel, M A
Vielzeuf, P
Abbott, T M C
Abdalla, F B
Allam, S
Annis, J
Bechtol, K
Benoit-Lévy, A
Bertin, E
Brooks, D
Buckley-Geer, E
Burke, D L
Carnero Rosell, A
Carrasco Kind, M
Carretero, J
Castander, F J
Crocce, M
Cunha, C E
D'Andrea, C B
da Costa, L N
Desai, S
Diehl, H T
Doel, P
Drlica-Wagner, A
Neto, A Fausti
Flaugher, B
Fosalba, P
Frieman, J
García-Bellido, J
Gaztanaga, E
Gerdes, D W
Giannantonio, T
Gruen, D
Gruendl, R A
Gutierrez, G
Honscheid, K
Jain, B
James, D J
Jeltema, T
Krause, E
Kuehn, K
Kuhlmann, S
Kuropatkin, N
Lahav, O
Li, T S
Lima, M
March, M
Marshall, J L
Martini, P
Melchior, P
Ogando, R L C
Plazas, A A
Romer, A K
Sanchez, E
Scarpine, V
Schindler, R
Schubnell, M
Sevilla-Noarbe, I
Smith, M
Soares-Santos, M
Sobreira, F
Suchyta, E
Swanson, M E C
Tarle, G
Thomas, D
Vikram, V
Walker, A R
Wechsler, R H
Affiliation
Univ Arizona, Dept PhysIssue Date
2018-06
Metadata
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OXFORD UNIV PRESSCitation
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, (DES Collaboration); Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data, Monthly Notices of the Royal Astronomical Society, Volume 477, Issue 2, 21 June 2018, Pages 2196–2208, https://doi.org/10.1093/mnras/sty787Rights
© 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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 Delta z similar to +/- 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.ISSN
0035-87111365-2966
Version
Final published versionSponsors
Northern California Chapter of the ARCS Foundation; U.S. Department of Energy [DE-AC02-76-5F00515]; DOE [DE-SC0015975]; Sloan Foundation [FG-2016-6443]; U.S. Department of Energy; U.S. National Science Foundation; Ministry of Science and Education of Spain; Science and Technology Facilities Council of the United Kingdom; Higher Education Funding Council for England; National Center for Supercomputing Applications at the University of Illinois at Urbana Champaign; Kavli Institute of Cosmological Physics at the University of Chicago; Center for Cosmology and Astro-Particle Physics at the Ohio State University; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University; Financiadora de Estudos e Projetos; Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico; Ministerio da Ciencia, Tecnologia e Inovacao; Deutsche Forschungsgemeinschaft; Argonne National Laboratory; University of California at Santa Cruz; University of Cambridge; Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid; University of Chicago; University College London; DES-Brazil Consortium; University of Edinburgh; Eidgenossische Technische Hochschule (ETH) Zurich; Fermi National Accelerator Laboratory; University of Illinois at Urbana-Champaign; Institut de Ciencies de l'Espai (IEEC/CSIC); Institut de Fisica d'Altes Energies; Lawrence Berkeley National Laboratory; Ludwig-Maximilians Universitat Munchen; associated Excellence Cluster Universe; University of Michigan; National Optical Astronomy Observatory; University of Nottingham; Ohio State University; University of Pennsylvania; University of Portsmouth; SLAC National Accelerator Laboratory; Stanford University; University of Sussex; Texas AM University; OzDES Membership Consortium; National Science Foundation [AST-1138766, AST-1536171]; MINECO [AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV-2012-0234, SEV-2012-0249, MDM-2015-0509]; ERDF funds from the European Union; CERCA program of the Generalitat de CatalunyaAdditional Links
https://academic.oup.com/mnras/article/477/2/2196/4953764ae974a485f413a2113503eed53cd6c53
10.1093/mnras/sty787