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    Core Cosmology Library: Precision Cosmological Predictions for LSST

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    Chisari_2019_ApJS_242_2.pdf
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    PDF
    Description:
    Final Published Version
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    Author
    Chisari, Nora Elisa
    Alonso, David
    Krause, Elisabeth
    Leonard, C. Danielle
    Bull, Philip
    Neveu, Jérémy
    Villarreal, Antonio
    Singh, Sukhdeep
    McClintock, Thomas
    Ellison, John
    Du, Zilong
    Zuntz, Joe
    Mead, Alexander
    Joudaki, Shahab
    Lorenz, Christiane S.
    Tröster, Tilman
    Sanchez, Javier
    Lanusse, Francois
    Ishak, Mustapha
    Hlozek, Renée
    Blazek, Jonathan
    Campagne, Jean-Eric
    Almoubayyed, Husni
    Eifler, Tim
    Kirby, Matthew
    Kirkby, David
    Plaszczynski, Stéphane
    Slosar, Anže
    Vrastil, Michal
    Wagoner, Erika L.
    Show allShow less
    Affiliation
    Univ Arizona, Dept Phys
    Univ Arizona, Med Ctr
    Univ Arizona, Dept Astron, Steward Observ
    Issue Date
    2019-05-01
    Keywords
    cosmology: theory
    dark energy
    large-scale structure of universe
    
    Metadata
    Show full item record
    Publisher
    IOP PUBLISHING LTD
    Citation
    Nora Elisa Chisari et al 2019 ApJS 242 2
    Journal
    ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES
    Rights
    Copyright © 2019. The American Astronomical Society. All rights reserved.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias, and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows us to establish a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing, and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a Python interface and publicly available at. https://github.com/LSSTDESC/CCL.
    ISSN
    0067-0049
    DOI
    10.3847/1538-4365/ab1658
    Version
    Final published version
    Sponsors
    Centre National de la Recherche Scientifique; National Energy Research Scientific Computing Center, a DOE Office of Science User Facility - Office of Science of the U.S. Department of Energy [DE-AC02-05CH11231]; STFC DiRAC HPC Facilities - UK BIS National E-infrastructure capital grants; UK particle physics grid - GridPP Collaboration; DOE [DE-AC02-76SF00515]; Science and Technology Facilities Council (STFC) through an Ernest Rutherford Fellowship [ST/P004474/1]; Beecroft fellowship; Royal Astronomical Society Research Fellowship; European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant [797794]; NSF [AST-1517768]; U.S. Department of Energy, Office of Science [DE-SC0019206]
    ae974a485f413a2113503eed53cd6c53
    10.3847/1538-4365/ab1658
    Scopus Count
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