Abstract
Shear peak statistics has gained a lot of attention recently as a practical alternative to the two-point statistics for constraining cosmological parameters. We perform a shear peak statistics analysis of the Dark Energy Survey (DES) Science Verification (SV) data, using weak gravitational lensing measurements from a 139 deg2 field. We measure the abundance of peaks identified in aperture mass maps, as a function of their signal-to-noise ratio, in the signal-to-noise range 0 < S/N < 4. To predict the peak counts as a function of cosmological parameters, we use a suite of N-body simulations spanning 158 models with varying Ωm and σ8, fixing w=-1, Ωb = 0.04, h = 0.7 and ns = 1, to which we have applied the DES SV mask and redshift distribution. In our fiducial analysis we measure σ8(Ωm/0.3)0.6 = 0.77 ± 0.07, after marginalizing over the shear multiplicative bias and the error on the mean redshift of the galaxy sample. We introduce models of intrinsic alignments, blending and source contamination by cluster members. These models indicate that peaks with S/N > 4 would require significant corrections, which is why we do not include them in our analysis. We compare our results to the cosmological constraints from the two-point analysis on the SV field and find them to be in good agreement in both the central value and its uncertainty. We discuss prospects for future peak statistics analysis with upcoming DES data.
Original language | English |
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Pages (from-to) | 3653-3673 |
Number of pages | 21 |
Journal | Monthly Notices of the Royal Astronomical Society |
Volume | 463 |
Issue number | 4 |
DOIs | |
State | Published - Dec 21 2016 |
Externally published | Yes |
Funding
We are grateful for the extraordinary contributions of our CTIO colleagues and the DECam Construction, Commissioning and Science Verification teams in achieving the excellent instrument and telescope conditions that have made this work possible. The success of this project also relies critically on the expertise and dedication of the DES Data Management group. Funding for the DES Projects has been provided by the US Department of Energy, the US National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology FacilitiesCouncil of theUnitedKingdom, theHigher Education Funding Council for England, the NationalCenter 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 Ciencia, 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, and Texas A&M University. The DES data management system is supported by the National Science Foundation under Grant Number AST-1138766. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2012-39559, ESP2013-48274, FPA2013-47986 and Centro de Excelencia Severo Ochoa SEV-2012-0234. Research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) including ERC grant agreements 240672, 291329 and 306478. This research used resources of the Calcul Quebec computing consortium, part of the Compute Canada network. DK acknowledges support from a European Research Council Advanced Grant FP7/291329. TK thanks the support of ETHZ ISG and the Brutus cluster team. OF was supported by SFB-Transregio 33 'The Dark Universe' by the Deutsche Forschungsgemeinschaft (DFG).
Funders | Funder number |
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Brutus cluster team | |
Centro de Excelencia Severo Ochoa | SEV-2012-0234 |
Collaborating Institutions are Argonne National Laboratory | |
Collaborating Institutions in the Dark Energy Survey | |
Institut de Ciències de l'Espai | |
Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University | |
National Science Foundation | AST-1138766 |
U.S. Department of Energy | |
University of Illinois at Urbana-Champaign | |
Stanford University | |
Fermilab | |
Lawrence Berkeley National Laboratory | |
University of California, Santa Cruz | |
University of Pennsylvania | |
Ohio State University | |
University of Chicago | |
University of Michigan | |
Texas A and M University | |
University of Portsmouth | |
National Centre for Supercomputing Applications | |
Seventh Framework Programme | 1138766, 240672, 306478, 291329 |
SLAC National Accelerator Laboratory | |
Science and Technology Facilities Council | |
Higher Education Funding Council for England | |
University College London | |
European Research Council | FP7/291329 |
University of Nottingham | |
University of Sussex | |
University of Edinburgh | |
Deutsche Forschungsgemeinschaft | |
Eidgenössische Technische Hochschule Zürich | |
Ministerio de Economía y Competitividad | FPA2013-47986, AYA2012-39559, ESP2013-48274 |
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 | |
Seventh Framework Programme | |
Ludwig-Maximilians-Universität München | |
Ministry of Education and Science of Ukraine | |
Institut de Física d'Altes Energies |
Keywords
- Cosmological parameter
- Cosmology: observations
- Dark matter
- Gravitational lensing: weak
- Methods: data analysis
- Methods: statistical