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Monte Carlo control loops for cosmic shear cosmology with DES Year 1 data

T. Kacprzak1,*, J. Herbel1, A. Nicola2, R. Sgier1, F. Tarsitano1, C. Bruderer1, A. Amara1, A. Refregier1, S. L. Bridle3 et al. (The DES Collaboration)

S. L. Bridle3, A. Drlica-Wagner4,5, D. Gruen6,7,8, W. G. Hartley9, B. Hoyle10,11, L. F. Secco12, J. Zuntz13, J. Annis4, S. Avila14, E. Bertin15,16, D. Brooks9, E. Buckley-Geer4, A. Carnero Rosell17,18, M. Carrasco Kind19,20, J. Carretero21, L. N. da Costa18,22, J. De Vicente17, S. Desai23, H. T. Diehl4, P. Doel9, J. García-Bellido14, E. Gaztanaga24,25, R. A. Gruendl19,20, J. Gschwend18,22, G. Gutierrez4, D. L. Hollowood26, K. Honscheid27,28, D. J. James29, M. Jarvis12, M. Lima30,18, M. A. G. Maia18,22, J. L. Marshall31, P. Melchior32, F. Menanteau19,20, R. Miquel33,21, F. Paz-Chinchón19,20, A. A. Plazas32, E. Sanchez17, V. Scarpine4, S. Serrano24,25, I. Sevilla-Noarbe17, M. Smith34, E. Suchyta35, M. E. C. Swanson20, G. Tarle36, V. Vikram37, and J. Weller38,10,11 (The DES Collaboration)

  • 1Institute for Particle Physics and Astrophysics, ETH Zurich, Wolfgang-Pauli-Strasse 27, CH-8093 Zurich, Switzerland
  • 2Department of Astrophysical Sciences, Princeton University, Princeton, New Jersey 08544, USA
  • 3Jodrell Bank Center for Astrophysics, School of Physics and Astronomy, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
  • 4Fermi National Accelerator Laboratory, P. O. Box 500, Batavia, Illinois 60510, USA
  • 5Kavli Institute for Cosmological Physics, University of Chicago, Chicago, Illinois 60637, USA
  • 6Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, California 94305, USA
  • 7Kavli Institute for Particle Astrophysics & Cosmology, P. O. Box 2450, Stanford University, Stanford, California 94305, USA
  • 8National Accelerator Laboratory, Menlo Park, California 94025, USA
  • 9Department of Physics & Astronomy, University College London, Gower Street, London WC1E 6BT, United Kingdom
  • 10Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, 85748 Garching, Germany
  • 11Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr. 1, 81679 München, Germany
  • 12Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
  • 13Institute for Astronomy, University of Edinburgh, Edinburgh EH9 3HJ, United Kingdom
  • 14Instituto de Fisica Teorica UAM/CSIC, Universidad Autonoma de Madrid, 28049 Madrid, Spain
  • 15CNRS, UMR 7095, Institut d’Astrophysique de Paris, F-75014 Paris, France
  • 16Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, Institut d’Astrophysique de Paris, F-75014 Paris, France
  • 17Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
  • 18Laboratório Interinstitucional de e-Astronomia—LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ—20921-400, Brazil
  • 19Department of Astronomy, University of Illinois at Urbana-Champaign, 1002 W. Green Street, Urbana, Illinois 61801, USA
  • 20National Center for Supercomputing Applications, 1205 West Clark Street, Urbana, Illinois 61801, USA
  • 21Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, 08193 Bellaterra (Barcelona) Spain
  • 22Observatório Nacional, Rua Gal. José Cristino 77, Rio de Janeiro, RJ—20921-400, Brazil
  • 23Department of Physics, IIT Hyderabad, Kandi, Telangana 502285, India
  • 24Institut d’Estudis Espacials de Catalunya (IEEC), 08034 Barcelona, Spain
  • 25Institute of Space Sciences (ICE, CSIC), Campus UAB, Carrer de Can Magrans, s/n, 08193 Barcelona, Spain
  • 26Santa Cruz Institute for Particle Physics, Santa Cruz, California 95064, USA
  • 27Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, Ohio 43210, USA
  • 28Department of Physics, The Ohio State University, Columbus, Ohio 43210, USA
  • 29Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, Massachusetts 02138, USA
  • 30Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo, CP 66318, São Paulo, SP 05314-970, Brazil
  • 31George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, and Department of Physics and Astronomy, Texas A&M University, College Station, Texas 77843, USA
  • 32Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, New Jersey 08544, USA
  • 33Institució Catalana de Recerca i Estudis Avançats, E-08010 Barcelona, Spain
  • 34School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, United Kingdom
  • 35Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
  • 36Department of Physics, University of Michigan, Ann Arbor, Michigan 48109, USA
  • 37Argonne National Laboratory, 9700 South Cass Avenue, Lemont, Illinois 60439, USA
  • 38Excellence Cluster Origins, Boltzmannstr. 2, 85748 Garching, Germany

  • *Corresponding author. tomasz.kacprzak@phys.ethz.ch
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Phys. Rev. D 101, 082003 – Published 27 April, 2020

DOI: https://doi.org/10.1103/PhysRevD.101.082003

Abstract

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. Monte Carlo control loops (MCCL) is a forward modeling method designed to tackle this problem. It relies on the ultra fast image generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. We present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum Cℓ and the redshift distribution n(z) of the background galaxy sample. The method includes maps of the systematic sources, point spread function (PSF), an approximate Bayesian computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and a fast method to estimate the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a nontomographic setting, we derive a set of Cℓ and n(z) curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of Ωm, σ8, and intrinsic alignment amplitude AIA, defined as S8DIA=σ8(Ωm/0.3)0.5DIA, where DIA=1−0.11(AIA−1). We find S8DIA=0.895−0.039+0.054, where systematics are at the level of roughly 60% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

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Phys. Rev. D 101, 082003– Published 27 April, 2020
  • Received 27 June 2019
  • Accepted 5 April 2020
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