In the past few years, several independent collaborations have presented cosmological constraints from tomographic cosmic shear analyses. These analyses differ in many aspects: the data sets, the shear and photometric redshift estimation algorithms, the theory model assumptions, and the inference pipelines. To assess the robustness of the existing cosmic shear results, we present in this paper a unified analysis of four of the recent cosmic shear surveys: the Deep Lens Survey (DLS), the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), the Science Verification data from the Dark Energy Survey (DES-SV), and the 450 deg2 release of the Kilo-Degree Survey (KiDS-450). By using a unified pipeline, we show how the cosmological constraints are sensitive to the various details of the pipeline. We identify several analysis choices that can shift the cosmological constraints by a significant fraction of the uncertainties. For our fiducial analysis choice, considering a Gaussian covariance, conservative scale cuts, assuming no baryonic feedback contamination, identical cosmological parameter priors and intrinsic alignment treatments, we find the constraints (mean, 16 per cent and 84 per cent confidence intervals) on the parameter S8 = σ8(Ωm/0.3)0.5 to be S8 = 0.942-0.045 (DLS), 0.657-0.070+0.071 (CFHTLenS), 0.844 -0.061 +0.062(DES-+0.046SV), and 0.755-0.049 +0.048 (KiDS-450). From the goodness-of-fit and the Bayesian evidence ratio, we determine that amongst the four surveys, the two more recent surveys, DES-SV and KiDS-450, have acceptable goodness of fit and are consistent with each other. The combined constraints are S8 = 0.790-0.041 +0.042, which is in good agreement with the first year of DES cosmic shear results and recent CMB constraints from the Planck satellite.
Bibliographical noteFunding Information:
We thank Hendrik Hildebrandt and Martin Kilbinger for helping with the KiDS-450 reanalysis. We thank Sebastian Bocquet, Francois Lanusse, and Javier Sanchez for help in the early stages of this project. We thank Weikang Lin and Mustapha Ishak for useful discussions regarding metrics for consistency. We thank Karan Vahi and Mats Rynge for support in using the Pegasus software. This paper has undergone internal review in the LSST Dark Energy Science Collaboration, with Bhuvnesh Jain, Niall MacCrann, and Marco Raveri as internal reviewers. CC was supported in part by the Kavli Institute for Cosmological Physics at the University of Chicago through grant NSF PHY-1125897 and an endowment from Kavli Foundation and its founder Fred Kavli. CH acknowledges support from the European Research Council under grant number 647112. Support for MS was provided by the University of California Riverside Office of Research and Economic Development through the FIELDS NASAMIRO programme. A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. MJJ acknowledges support for the current research from the National Research Foundation of Korea under the programme 2017R1A2B2004644 and 2017R1A4A1015178. RM is supported by the Department of Energy Cosmic Frontier programme, grant DE-SC0010118. SJ acknowledges support from the Beecroft Trust and ERC 693024. AIM is advised by David W. Hogg and was supported by National Science Foundation grant AST-1517237. Part of this work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. This work was performed at the Aspen Center for Physics, which is supported by National Science Foundation grant PHY-1607611. The DESC acknowledges ongoing support from the Institut National de Physique Nucléaire et de Physique des Particules in France; the Science & Technology Facilities Council in the United Kingdom; and the Department of Energy, the National Science Foundation, and the LSST Corporation in the United States. DESC uses resources of the IN2P3 Computing Center (CC-IN2P3-Lyon/Villeurbanne-France) funded by the Centre National de la Recherche Scientifique; the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231; STFC DiRAC HPC Facilities, funded by UK BIS National E-infrastructure capital grants; and the UK particle physics grid, supported by the GridPP Collaboration. This work was performed in part under DOE Contract DE-AC02-76SF00515. CFHTLenS: This work is based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This research used the facilities of the Canadian Astronomy Data Centre operated by the National Research Council of Canada with the support of the Canadian Space Agency. CFHTLenS data processing was made possible thanks to significant computing support from the NSERC Research Tools and Instruments grant programme. DES-SV: This project used public archival data from the Dark Energy Survey (DES). 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 Eidgen össische 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 OzDES Membership Consortium, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, and Texas A&M University. 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. KiDS-450: This work is based on data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under programme IDs 177.A-3016, 177.A-3017, and 177.A-3018. We use cosmic shear measurements from the Kilo-Degree Survey (Kuijken et al. 2015; Fenech Conti et al. 2017; Hildebrandt et al. 2017), hereafter referred to as KiDS. The KiDS data are processed by THELI (Erben et al. 2013) and Astro-WISE (Begeman et al. 2013, de Jong et al. 2015). Shears are measured using lensfit (Miller et al. 2013), and photometric redshifts are obtained from PSF-matched photometry and calibrated using external overlapping spectroscopic surveys (see Hildebrandt et al. 2017). The contributions from the primary authors are listed below. CC led the main analysis and writing of this paper. MW wrote the main software package WLPIPE which integrates the python scripts using the Pegasus workflow engine. SD helped with the pipeline development, covariance assessment, comparison metrics, pipeline testing, and editing.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science