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Dark Energy Survey Year 3 Results: Constraints on extensions to $Łambda$CDM with weak lensing and galaxy clustering

, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and . (2022)cite arxiv:2207.05766Comment: 45 pages, 25 figures, data available at https://dev.des.ncsa.illinois.edu/releases/y3a2/Y3key-extensions.

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Dark Energy Survey Year 3 results: cosmology from combined galaxy clustering and lensing -- validation on cosmological simulations, , , , , , , , , and 107 other author(s). (2021)cite arxiv:2105.13547Comment: 29 pages, 10 figures, see this URL for the full DES Y3 cosmology release: https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/.Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology, , , , , , , , , and 104 other author(s). (2020)cite arxiv:2011.03407Comment: see https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ for the full DES Y3 cosmology release.Catalyst: A DSIP Design Flow Development in Industry., , , , , , and . ISSS, page 122-127. ACM / IEEE Computer Society, (1999)Dark Energy Survey Year 3 Results: Cosmology from Cosmic Shear and Robustness to Data Calibration, , , , , , , , , and 138 other author(s). (2021)cite arxiv:2105.13543Comment: 42 pages, 19 figures.Dark Energy Survey Year 3 Results: Constraints on cosmological parameters and galaxy bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample, , , , , , , , , and 131 other author(s). (2021)cite arxiv:2105.13545Comment: 27 pages, 19 figures, comments welcome.Dark Energy Survey Year 3 results: Cosmological constraints from galaxy clustering and galaxy-galaxy lensing using the MagLim lens sample, , , , , , , , , and 134 other author(s). (2021)cite arxiv:2105.13546Comment: 25 pages, 16 figures, to be submitted to PRD. See https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ for the full DES Y3 cosmology release.A machine learning approach to galaxy properties: Joint redshift - stellar mass probability distributions with Random Forest., , , , , , , , , and 63 other author(s). CoRR, (2020)Data science curriculum in the iField, , , , , , , , , and 3 other author(s). Journal of the American Society for Information Science. American Society for Information Science, (July 2022)Publisher: Association for Information Science and Technology (ASIS&T).Dark Energy Survey Year 3 Results: Constraints on extensions to $Łambda$CDM with weak lensing and galaxy clustering, , , , , , , , , and 152 other author(s). (2022)cite arxiv:2207.05766Comment: 45 pages, 25 figures, data available at https://dev.des.ncsa.illinois.edu/releases/y3a2/Y3key-extensions.Dark Energy Survey Year 3 Results: Weak Lensing Shape Catalogue, , , , , , , , , and 92 other author(s). (2020)cite arxiv:2011.03408Comment: Submitted to MNRAS. See https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ for the full DES Y3 cosmology release.