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 Câ"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 Câ"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.
| Original language | English |
|---|---|
| Article number | 082003 |
| Journal | Physical Review D |
| Volume | 101 |
| Issue number | 8 |
| DOIs | |
| State | Published - Apr 15 2020 |
Funding
We thank Joel Bergé, Chihway Chang and Lukas Gamper for crucial contributions to the development of ufig and the MCCL method. We thank Janis Fluri for helpful conversations and help with deep learning aspect of PSF modeling. We thank Uwe Schmitt and Jarunan Panyasantisuk for informatics support. We acknowledge support by Grant No. 200021_169130 from the Swiss National Science Foundation. We acknowledge the support of Euler cluster by High Performance Computing Group from ETHZ Scientific IT Services, as well as the support of the Piz Daint cluster by the Swiss National Supercomputing Center (CSCS). Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministério da Ciência, Tecnologia e Inovação, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciències de l’Espai (IEEC/CSIC), the Institut de Física d’Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, Texas A&M University, and the OzDES Membership Consortium. Based in part on observations at Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The DES data management system is supported by the National Science Foundation under Grants No, AST-1138766 and No. AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under Grants No. AYA2015-71825, No. ESP2015-66861, No. FPA2015-68048, No. SEV-2016-0588, No. SEV-2016-0597, and No. MDM-2015-0509, some of which include ERDF funds from the European Union. I. F. A. E. is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013) including ERC Grant agreements No. 240672, No. 291329, and No. 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) e-Universe (CNPq grant No. 465376/2014-2). This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.
| Funders | Funder number |
|---|---|
| Collaborating Institutions in the Dark Energy Survey | |
| ETHZ Scientific IT Services | |
| European Union’s Seventh Framework Program | |
| FP7/2007 | |
| Fermi Research Alliance, LLC | DE-AC02-07CH11359 |
| INCT | |
| Kavli Institute of Cosmological Physics at the University of Chicago | |
| Ministry of Science and Education of Spain | |
| Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University | |
| National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign | |
| U.S. National Science Foundation | |
| National Science Foundation | AST-1138766, AST-1536171 |
| U.S. Department of Energy | |
| Office of Science | |
| High Energy Physics | |
| Seventh Framework Programme | 1138766, 240672, 306478, 291329 |
| Higher Education Funding Council for England | |
| Center for Cosmology and Astroparticle Physics, Ohio State University | |
| Instituto Nacional de Ciência e Tecnologia Midas | |
| Science and Technology Facilities Council | |
| European Commission | |
| European Research Council | |
| Deutsche Forschungsgemeinschaft | |
| Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung | |
| Generalitat de Catalunya | |
| Ministerio de Economía y Competitividad | SEV-2016-0588, SEV-2016-0597, ESP2015-66861, MDM-2015-0509, FPA2015-68048, AYA2015-71825 |
| Ministério da Ciência, Tecnologia e Inovação | |
| Conselho Nacional de Desenvolvimento Científico e Tecnológico | 465376/2014-2 |
| Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro | |
| Financiadora de Estudos e Projetos | |
| European Regional Development Fund | |
| National Supercomputing Center of Tianjin |