Dark Energy Survey Year 3 results: cosmology with moments of weak lensing mass maps – validation on simulations
ABSTRACT We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The second moment, or variances, of the convergence as a function of smoothing scale contains information similar to standard shear two-point statistics. The third momen...
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Published in | Monthly notices of the Royal Astronomical Society Vol. 498; no. 3; pp. 4060 - 4087 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English Norwegian |
Published |
United Kingdom
Oxford University Press
01.11.2020
Royal Astronomical Society |
Subjects | |
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Abstract | ABSTRACT
We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The second moment, or variances, of the convergence as a function of smoothing scale contains information similar to standard shear two-point statistics. The third moment, or the skewness, contains additional non-Gaussian information. The analysis is geared towards the third year (Y3) data from the Dark Energy Survey (DES), but the methodology can be applied to other weak lensing data sets. We present the formalism for obtaining the convergence maps from the measured shear and for obtaining the second and third moments of these maps given partial sky coverage. We estimate the covariance matrix from a large suite of numerical simulations. We test our pipeline through a simulated likelihood analyses varying 5 cosmological parameters and 10 nuisance parameters and identify the scales where systematic or modelling uncertainties are not expected to affect the cosmological analysis. Our simulated likelihood analysis shows that the combination of second and third moments provides a 1.5 per cent constraint on S8 ≡ σ8(Ωm/0.3)0.5 for DES Year 3 data. This is 20 per cent better than an analysis using a simulated DES Y3 shear two-point statistics, owing to the non-Gaussian information captured by the inclusion of higher order statistics. This paper validates our methodology for constraining cosmology with DES Year 3 data, which will be presented in a subsequent paper. |
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AbstractList | ABSTRACT
We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The second moment, or variances, of the convergence as a function of smoothing scale contains information similar to standard shear two-point statistics. The third moment, or the skewness, contains additional non-Gaussian information. The analysis is geared towards the third year (Y3) data from the Dark Energy Survey (DES), but the methodology can be applied to other weak lensing data sets. We present the formalism for obtaining the convergence maps from the measured shear and for obtaining the second and third moments of these maps given partial sky coverage. We estimate the covariance matrix from a large suite of numerical simulations. We test our pipeline through a simulated likelihood analyses varying 5 cosmological parameters and 10 nuisance parameters and identify the scales where systematic or modelling uncertainties are not expected to affect the cosmological analysis. Our simulated likelihood analysis shows that the combination of second and third moments provides a 1.5 per cent constraint on S8 ≡ σ8(Ωm/0.3)0.5 for DES Year 3 data. This is 20 per cent better than an analysis using a simulated DES Y3 shear two-point statistics, owing to the non-Gaussian information captured by the inclusion of higher order statistics. This paper validates our methodology for constraining cosmology with DES Year 3 data, which will be presented in a subsequent paper. We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The second moment, or variances, of the convergence as a function of smoothing scale contains information similar to standard shear two-point statistics. The third moment, or the skewness, contains additional non-Gaussian information. The analysis is geared towards the third year (Y3) data from the Dark Energy Survey (DES), but the methodology can be applied to other weak lensing data sets. We present the formalism for obtaining the convergence maps from the measured shear and for obtaining the second and third moments of these maps given partial sky coverage. We estimate the covariance matrix from a large suite of numerical simulations. We test our pipeline through a simulated likelihood analyses varying 5 cosmological parameters and 10 nuisance parameters and identify the scales where systematic or modelling uncertainties are not expected to affect the cosmological analysis. Our simulated likelihood analysis shows that the combination of second and third moments provides a 1.5 percent constraint on S8 ≡ σ8(Ωm/0.3)0.5 for DES Year 3 data. This is 20 percent better than an analysis using a simulated DES Y3 shear two-point statistics, owing to the non-Gaussian information captured by the inclusion of higher order statistics. This paper validates our methodology for constraining cosmology with DES Year 3 data, which will be presented in a subsequent paper. |
Author | Annis, J Gruendl, R A Avila, S Marshall, J L MacCrann, N Estrada, J Fosalba, P Sánchez, C Frieman, J Palmese, A Gerdes, D W García-Bellido, J Miquel, R Harrison, I Melchior, P Carnero Rosell, A Santiago, S Troxel, M A Schubnell, M Gaztanaga, E Diehl, H T Krause, E Tarle, G Jain, B Gruen, D McClintock, T Kuehn, K Bacon, D Burke, D L Buckley-Geer, E Menanteau, F Suchyta, E Sanchez, E Carretero, J Soares-Santos, M Gschwend, J Secco, L Paz-Chinchón, F da Costa, L N Cawthon, R Chang, C James, D J Carrasco Kind, M Swanson, M E C Whiteway, L Eifler, T F Zuntz, J Scarpine, V Brooks, D Doel, P Smith, M Crocce, M Plazas, A A Thomas, D Ferrero, I De Vicente, J Desai, S Gutierrez, G Maia, M A G Evrard, A E Jeffrey, N Abbott, T M C Allam, S March, M Friedrich, O DeRose, J Sevilla-Noarbe, I Johnson, M D Lima, M Everett, S Gatti, M |
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orcidid: 0000-0001-6082-8529 surname: Soares-Santos fullname: Soares-Santos, M – sequence: 66 givenname: E orcidid: 0000-0002-7047-9358 surname: Suchyta fullname: Suchyta, E – sequence: 67 givenname: M E C surname: Swanson fullname: Swanson, M E C – sequence: 68 givenname: G surname: Tarle fullname: Tarle, G – sequence: 69 givenname: D orcidid: 0000-0002-6325-5671 surname: Thomas fullname: Thomas, D – sequence: 70 givenname: M A orcidid: 0000-0002-5622-5212 surname: Troxel fullname: Troxel, M A – sequence: 71 givenname: J orcidid: 0000-0001-9789-9646 surname: Zuntz fullname: Zuntz, J |
BackLink | https://www.osti.gov/biblio/1668095$$D View this record in Osti.gov |
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CorporateAuthor | Des Collaboration Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States) Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States) Univ. of Michigan, Ann Arbor, MI (United States) |
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Keywords | gravitational lensing: weak cosmology: observations large-scale structure of Universe |
Language | English Norwegian |
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Notes | NFR/287772 AC02-07CH11359; SC0019193; AC05-00OR22725 USDOE Office of Science (SC), High Energy Physics (HEP) FERMILAB-PUB-19-576-A-AD-AE-SCD; arXiv:1911.05568 |
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We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The second moment, or... We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The second moment, or variances, of... |
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SubjectTerms | ASTRONOMY AND ASTROPHYSICS cosmology: observations gravitational lensing: weak large-scale structure of Universe |
Title | Dark Energy Survey Year 3 results: cosmology with moments of weak lensing mass maps – validation on simulations |
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