Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. Validation on simulations

M. Gatti, N. Jeffrey, L. Whiteway, J. Williamson, B. Jain, V. Ajani, D. Anbajagane, G. Giannini, C. Zhou, A. Porredon, J. Prat, M. Yamamoto, J. Blazek, T. Kacprzak, S. Samuroff, A. Alarcon, A. Amon, K. Bechtol, M. Becker, G. BernsteinA. Campos, C. Chang, R. Chen, A. Choi, C. Davis, J. Derose, H. T. Diehl, S. Dodelson, C. Doux, K. Eckert, J. Elvin-Poole, S. Everett, A. Ferte, D. Gruen, R. Gruendl, I. Harrison, W. G. Hartley, K. Herner, E. M. Huff, M. Jarvis, N. Kuropatkin, P. F. Leget, N. Maccrann, J. Mccullough, J. Myles, A. Navarro-Alsina, S. Pandey, M. Raveri, R. P. Rollins, A. Roodman, C. Sanchez, L. F. Secco, I. Sevilla-Noarbe, E. Sheldon, T. Shin, M. Troxel, I. Tutusaus, T. N. Varga, B. Yanny, B. Yin, Y. Zhang, J. Zuntz, M. Aguena, O. Alves, J. Annis, D. Brooks, J. Carretero, F. J. Castander, R. Cawthon, M. Costanzi, L. N. Da Costa, M. E.S. Pereira, A. E. Evrard, B. Flaugher, P. Fosalba, J. Frieman, J. García-Bellido, D. W. Gerdes, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, D. L. Hollowood, K. Honscheid, D. J. James, K. Kuehn, O. Lahav, S. Lee, J. L. Marshall, J. Mena-Fernández, F. Menanteau, R. Miquel, R. L.C. Ogando, M. E.S. Pereira, A. Pieres, A. A. Plazas Malagón, E. Sanchez, M. Smith, E. Suchyta, M. E.C. Swanson, G. Tarle, N. Weaverdyck, J. Weller, P. Wiseman

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15 Scopus citations

Abstract

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulation-based analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogs of the Dark Energy Survey (DES). We implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven νwCDM cosmological parameters, and it forward models the most relevant sources of systematics of 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 likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST, and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 percent, 15 percent, and 90 percent for S8, ωm, and the figure-of-merit FoMS8,ωm, respectively. We further find that non-Gaussian statistics improve constraints on w and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogs for each survey. In a companion paper we present an application to DES Year 3 data.

Original languageEnglish
Article number063534
JournalPhysical Review D
Volume109
Issue number6
DOIs
StatePublished - Mar 15 2024

Funding

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 Proposition 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 (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.

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