Abstract
We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven w Cold Dark Matter (wCDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (S8,ωm) is improved by 70% (ΛCDM) and 90% (wCDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter S8σ8(ωm/0.3)0.5, obtaining S8=0.794±0.017 (ΛCDM) and S8=0.817±0.021 (wCDM), and a ∼10% constraint on ωm, obtaining ωm=0.259±0.025 (ΛCDM) and ωm=0.273±0.029 (wCDM). In the context of the wCDM scenario, these statistics also strengthen the constraints on the parameter w, obtaining w<-0.72. The constraints from different statistics are shown to be internally consistent (with a p-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2σ.
| Original language | English (US) |
|---|---|
| Article number | 063504 |
| Journal | Physical Review D |
| Volume | 111 |
| Issue number | 6 |
| Early online date | Mar 3 2025 |
| DOIs | |
| State | Published - Mar 15 2025 |
ASJC Scopus subject areas
- Nuclear and High Energy Physics
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In: Physical Review D, Vol. 111, No. 6, 063504, 15.03.2025.
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Dark Energy Survey Year 3 results
T2 - Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. II. cosmological results
AU - (Dark Energy Survey)
AU - Gatti, M.
AU - Campailla, G.
AU - Jeffrey, N.
AU - Whiteway, L.
AU - Porredon, A.
AU - Prat, J.
AU - Williamson, J.
AU - Raveri, M.
AU - Jain, B.
AU - Ajani, V.
AU - Giannini, G.
AU - Yamamoto, M.
AU - Zhou, C.
AU - Blazek, J.
AU - Anbajagane, D.
AU - Samuroff, S.
AU - Kacprzak, T.
AU - Alarcon, A.
AU - Amon, A.
AU - Bechtol, K.
AU - Becker, M.
AU - Bernstein, G.
AU - Campos, A.
AU - Chang, C.
AU - Chen, R.
AU - Choi, A.
AU - Davis, C.
AU - Derose, J.
AU - Diehl, H. T.
AU - Dodelson, S.
AU - Doux, C.
AU - Eckert, K.
AU - Elvin-Poole, J.
AU - Everett, S.
AU - Ferte, A.
AU - Gruen, D.
AU - Gruendl, R.
AU - Harrison, I.
AU - Hartley, W. G.
AU - Herner, K.
AU - Huff, E. M.
AU - Jarvis, M.
AU - Kuropatkin, N.
AU - Leget, P. F.
AU - MacCrann, N.
AU - McCullough, J.
AU - Myles, J.
AU - Navarro-Alsina, A.
AU - Pandey, S.
AU - Rollins, R. P.
N1 - 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, Funda\u00E7\u00E3o Carlos Chagas Filho de Amparo \u00E0 Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Cient\u00EDfico e Tecnol\u00F3gico and the Minist\u00E9rio da Ci\u00EAncia, Tecnologia e Inova\u00E7\u00E3o, 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 Energ\u00E9ticas, Medioambientales y Tecnol\u00F3gicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgen\u00F6ssische Technische Hochschule (ETH) Z\u00FCrich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ci\u00E8ncies de l\u2019Espai (IEEC/CSIC), the Institut de F\u00EDsica d\u2019Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universit\u00E4t M\u00FCnchen and the associated Excellence Cluster Universe, the University of Michigan, NSF\u2019s NOIRLab, 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 at NSF\u2019s NOIRLab (NOIRLab Prop. ID 2012B-0001; PI: J. Frieman), which is managed 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 MICINN under Grants No. ESP2017-89838, No. PGC2018-094773, No. PGC2018-102021, No. SEV-2016-0588, No. SEV-2016-0597, and No. MDM-2015-0509, some of which include ERDF funds from the European Union. I.\u2009F.\u2009A.\u2009E. 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\u2019s Seventh Framework Program (Grant No. FP7/2007-2013) including ERC Grant Agreements No. 240672, No. 291329, and No. 306478. We acknowledge support from the Brazilian Instituto Nacional de Ci\u00EAncia e Tecnologia (INCT) do e-Universo (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 Gower Street simulations were generated under the DiRAC project p153 \u201CLikelihood-free inference with the Dark Energy Survey\u201D (ACSP255/ACSC1) using DiRAC (STFC) HPC facilities . 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, Funda\u00E7\u00E3o Carlos Chagas Filho de Amparo \u00E0 Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Cient\u00EDfico e Tecnol\u00F3gico and the Minist\u00E9rio da Ci\u00EAncia, Tecnologia e Inova\u00E7\u00E3o, 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 Energ\u00E9ticas, Medioambientales y Tecnol\u00F3gicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgen\u00F6ssische Technische Hochschule (ETH) Z\u00FCrich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ci\u00E8ncies de l\u2019Espai (IEEC/CSIC), the Institut de F\u00EDsica d\u2019Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universit\u00E4t M\u00FCnchen and the associated Excellence Cluster Universe, the University of Michigan, NSF\u2019s NOIRLab, 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 at NSF\u2019s NOIRLab (NOIRLab Prop. ID 2012B-0001; PI: J. Frieman), which is managed 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 MICINN under Grants No. ESP2017-89838, No. PGC2018-094773, No. PGC2018-102021, 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\u2019s Seventh Framework Program (Grant No. FP7/2007-2013) including ERC Grant Agreements No. 240672, No. 291329, and No. 306478. We acknowledge support from the Brazilian Instituto Nacional de Ci\u00EAncia e Tecnologia (INCT) do e-Universo (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 Gower Street simulations were generated under the DiRAC project p153 \u201CLikelihood-free inference with the Dark Energy Survey\u201D (ACSP255/ACSC1) using DiRAC (STFC) HPC facilities [92].
PY - 2025/3/15
Y1 - 2025/3/15
N2 - We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven w Cold Dark Matter (wCDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (S8,ωm) is improved by 70% (ΛCDM) and 90% (wCDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter S8σ8(ωm/0.3)0.5, obtaining S8=0.794±0.017 (ΛCDM) and S8=0.817±0.021 (wCDM), and a ∼10% constraint on ωm, obtaining ωm=0.259±0.025 (ΛCDM) and ωm=0.273±0.029 (wCDM). In the context of the wCDM scenario, these statistics also strengthen the constraints on the parameter w, obtaining w<-0.72. The constraints from different statistics are shown to be internally consistent (with a p-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2σ.
AB - We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven w Cold Dark Matter (wCDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (S8,ωm) is improved by 70% (ΛCDM) and 90% (wCDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter S8σ8(ωm/0.3)0.5, obtaining S8=0.794±0.017 (ΛCDM) and S8=0.817±0.021 (wCDM), and a ∼10% constraint on ωm, obtaining ωm=0.259±0.025 (ΛCDM) and ωm=0.273±0.029 (wCDM). In the context of the wCDM scenario, these statistics also strengthen the constraints on the parameter w, obtaining w<-0.72. The constraints from different statistics are shown to be internally consistent (with a p-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2σ.
UR - https://www.scopus.com/pages/publications/105001872459
UR - https://www.scopus.com/pages/publications/105001872459#tab=citedBy
U2 - 10.1103/PhysRevD.111.063504
DO - 10.1103/PhysRevD.111.063504
M3 - Article
AN - SCOPUS:105001872459
SN - 2470-0010
VL - 111
JO - Physical Review D
JF - Physical Review D
IS - 6
M1 - 063504
ER -