class_sz I: Overview
class_sz is a versatile, robust and efficient code, in C and Python, optimized to compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks...
| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2024/03/epjconf_mmUniverse2023_00008.pdf |
| _version_ | 1797235296610287616 |
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| author | Bolliet B. Kusiak A. McCarthy F. Sabyr A. Surrao K. Hill J.C. Chluba J. Ferraro S. Hadzhiyska B. Han D. Macías-Pérez J.F. Madhavacheril M. Maniyar A. Mehta Y. Pandey S. Schaan E. Sherwin B. Mancini A. Spurio Zubeldia Í. |
| author_facet | Bolliet B. Kusiak A. McCarthy F. Sabyr A. Surrao K. Hill J.C. Chluba J. Ferraro S. Hadzhiyska B. Han D. Macías-Pérez J.F. Madhavacheril M. Maniyar A. Mehta Y. Pandey S. Schaan E. Sherwin B. Mancini A. Spurio Zubeldia Í. |
| author_sort | Bolliet B. |
| collection | DOAJ |
| description | class_sz is a versatile, robust and efficient code, in C and Python, optimized to compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks (https://github.com/CLASS-SZ/notebooks). It will be presented in full detail in paper II. Here we give a brief overview of key features and usage. |
| first_indexed | 2024-04-24T16:45:42Z |
| format | Article |
| id | doaj.art-ffcdfbc6987b4d5bba221a17bb7a4942 |
| institution | Directory Open Access Journal |
| issn | 2100-014X |
| language | English |
| last_indexed | 2024-04-24T16:45:42Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | EPJ Web of Conferences |
| spelling | doaj.art-ffcdfbc6987b4d5bba221a17bb7a49422024-03-29T08:31:00ZengEDP SciencesEPJ Web of Conferences2100-014X2024-01-012930000810.1051/epjconf/202429300008epjconf_mmUniverse2023_00008class_sz I: OverviewBolliet B.0Kusiak A.1McCarthy F.2Sabyr A.3Surrao K.4Hill J.C.5Chluba J.6Ferraro S.7Hadzhiyska B.8Han D.9Macías-Pérez J.F.10Madhavacheril M.11Maniyar A.12Mehta Y.13Pandey S.14Schaan E.15Sherwin B.16Mancini A. Spurio17Zubeldia Í.18Kavli Institute for Cosmology, University of CambridgeDepartment of Physics, Columbia UniversityKavli Institute for Cosmology, University of CambridgeDepartment of Physics, Columbia UniversityDepartment of Physics, Columbia UniversityCenter for Computational Astrophysics, Flatiron InstituteJodrell Bank Centre for Astrophysics, Alan Turing Building, University of ManchesterLawrence Berkeley National LaboratoryBerkeley Center for Cosmological Physics, Department of Physics, University of CaliforniaKavli Institute for Cosmology, University of CambridgeLaboratoire de Physique Subatomique et de Cosmologie, Universite Grenoble-Alpes, CNRS/IN2P3Department of Physics and Astronomy, University of PennsylvaniaSLAC National Accelerator LaboratorySchool of Earth and Space Exploration, Arizona State UniversityDepartment of Physics, Columbia UniversitySLAC National Accelerator LaboratoryKavli Institute for Cosmology, University of CambridgeMullard Space Science Laboratory, University College LondonKavli Institute for Cosmology, University of Cambridgeclass_sz is a versatile, robust and efficient code, in C and Python, optimized to compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks (https://github.com/CLASS-SZ/notebooks). It will be presented in full detail in paper II. Here we give a brief overview of key features and usage.https://www.epj-conferences.org/articles/epjconf/pdf/2024/03/epjconf_mmUniverse2023_00008.pdf |
| spellingShingle | Bolliet B. Kusiak A. McCarthy F. Sabyr A. Surrao K. Hill J.C. Chluba J. Ferraro S. Hadzhiyska B. Han D. Macías-Pérez J.F. Madhavacheril M. Maniyar A. Mehta Y. Pandey S. Schaan E. Sherwin B. Mancini A. Spurio Zubeldia Í. class_sz I: Overview EPJ Web of Conferences |
| title | class_sz I: Overview |
| title_full | class_sz I: Overview |
| title_fullStr | class_sz I: Overview |
| title_full_unstemmed | class_sz I: Overview |
| title_short | class_sz I: Overview |
| title_sort | class sz i overview |
| url | https://www.epj-conferences.org/articles/epjconf/pdf/2024/03/epjconf_mmUniverse2023_00008.pdf |
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