Agradecimentos: The ETH Zurich Cosmology group acknowledges support by grants 200021_192243 and 200021_169130 of the Swiss National Science Foundation. Some of the results in this paper have been derived using the healpy and HEALPix packages. In this study, we made use of the functionalities...

Agradecimentos: The ETH Zurich Cosmology group acknowledges support by grants 200021_192243 and 200021_169130 of the Swiss National Science Foundation. Some of the results in this paper have been derived using the healpy and HEALPix packages. In this study, we made use of the functionalities provided by numpy (Walt, Colbert & Varoquaux 2011), scipy (Virtanen et al. 2020), matplotlib (Hunter 2007), scikit-learn (Pedregosa et al. 2011), PolyChord. We thank Antony Lewis for the distribution of GetDist, on which we relied to produce some of the plots presented in this work (Lewis 2019). We would also like to thank Uwe Schmitt from ETH Zürich for his support with the GitLab server and CI engine. 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 Physic at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnologico and the Ministerio da Ciencia, Tecnologia e Inovacao, 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 Tecnologicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenoessische Technische Hochschule (ETH) Zurich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciencies de l’Espai (IEEC/CSIC), the Institut de Fisica d’Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität Muenchen and the associated Excellence Cluster Universe, the University of Michigan, NFS’s 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’s 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. Based on observations obtained with Planck,11 an ESA science mission with instruments and contributions directly funded by ESA Member States, NASA, and Canada

Abstract: We constrain the matter density Omega(m) and the amplitude of density fluctuations sigma(s) within the Lambda CDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey...

Abstract: We constrain the matter density Omega(m) and the amplitude of density fluctuations sigma(s) within the Lambda CDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including cross-peaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forward-modelling scheme to create a likelihood of these statistics using N-body simulations, using a Gaussian process emulator. We take into account the uncertainty from the remaining, largely unconstrained Lambda CDM parameters (Omega(b), n(s), and h). We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional non-Gaussian information leads to a tightening of the constraints on the structure growth parameter yielding S-8 sigma(8)root Omega(m)/0.3 = 0.797(-0.013)(+0.015) (68 per cent confidence limits), with a precision of 1.8 per cent, an improvement of 38 per cent compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be in agreement with each other and no significant difference in S-8 is recorded. We find a mild tension of 1.5 a between our study and the results from Planck 2018, with our analysis yielding a lower S-8. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment A(IA) and S-8, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data

FINANCIADORA DE ESTUDOS E PROJETOS - FINEP

FUNDAÇÃO CARLOS CHAGAS FILHO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIRO - FAPERJ

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

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