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HI constraints from the cross-correlation of eBOSS galaxies and Green Bank Telescope intensity maps

, , , , , , , , , , , , , , , , , , , , and . (2021)cite arxiv:2102.04946Comment: 16 pages, 15 figures, 1 table; submitted to MNRAS.

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HI intensity mapping correlation function from UNIT simulations: BAO and observationally induced anisotropy, , , , , , and . (2021)cite arxiv:2105.10454Comment: Comments welcome; 14 pages, 9 figures.Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies., , , , , , , , , and 38 other author(s). CoRR, (2023)Primordial Non-Gaussianity, , , , , , , , , and 168 other author(s). (2019)cite arxiv:1903.04409Comment: 5 pages + references; Submitted to the Astro2020 call for science white papers. This version: fixed author list.Discovery of a Candidate Binary Supermassive Black Hole in a Periodic Quasar from Circumbinary Accretion Variability, , , , , , , , , and 61 other author(s). (2020)cite arxiv:2008.12317Comment: resubmitted to MNRAS after addressing referee reports; comments are welcome.HI constraints from the cross-correlation of eBOSS galaxies and Green Bank Telescope intensity maps, , , , , , , , , and 11 other author(s). (2021)cite arxiv:2102.04946Comment: 16 pages, 15 figures, 1 table; submitted to MNRAS.Load Sharing Dynamic Routing in a Telephone Network, and . page 4.1-4.7. (1985)Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs., , , , , , , , , and 74 other author(s). Astron. Comput., (2020)Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe, , , , , , , , , and 67 other author(s). (2020)cite arxiv:2007.15026Comment: 24 pages, 18 figures, 2 tables. submitted to MNRAS. A brief video summary of this paper is available at https://www.youtube.com/watch?v=QbeNwk5papU.Constraints on Decaying Dark Matter with DES-Y1 and external data, , , , , , , , , and 75 other author(s). (2020)cite arxiv:2011.04606Comment: 23 pages, 11 figures. DES extensions group.Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects., , , , , , , , , and 49 other author(s). CoRR, (2020)