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Conference on Science at the Sanford Underground Research Facility

May 14 – 17, 2024
SD Mines
US/Mountain timezone

Session

Plenary: Neutrinos

May 14, 2024, 10:30 AM
CB 204 E&W (SD Mines)

CB 204 E&W

SD Mines

Conveners

Plenary: Neutrinos

  • Juergen Reichenbacher (South Dakota School of Mines and Technology)

Description

Zoom: https://sdsmt.zoom.us/j/93762102151?pwd=Nm9MWm91b0ZxN2YycUg4b251MU9TQT09

Presentation materials

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  1. 72. The Deep Underground Neutrino Experiment DUNE: Prospective Physics Program and Status
    Dr Kevin Wood (Lawrence Berkeley National Laboratory)
    5/14/24, 10:30 AM
    Neutrino Oscillations
    Oral

    The Deep Underground Neutrino Experiment (DUNE) is the future flagship particle physics experiment of the US HEP program. It will measure the mass ordering within a few years, will make precision measurements of various neutrino oscillation parameters, and has the potential to make measurements of CP-violation in the neutrino sector with >5 (>3) sigma significance for 50% (>75%) of the...

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  2. 104. Probing Astro- and Particle Physics with Supernova and Solar Neutrinos at SURF
    Daniel Pershey (Florida State University)
    5/14/24, 11:00 AM
    Supernova & Solar Neutrinos
    Oral

    Many mysteries still surround the neutrino.  Despite being the most common massive particle in the universe, its basic properties, such as their mass, are still unknown, as they interact very rarely with matter.  They are produced copiously during the life cycles of stars.  Measuring neutrinos from the sun, pioneered by the Davis experiment at SURF, has confirmed the nuclear fusion processes...

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  3. 71. Pushing Rare Event Search to the Limit with Machine Learning Algorithms
    Aobo Li (University of California San Diego)
    5/14/24, 11:30 AM
    Advanced Data Analysis
    Oral

    Rare event searches allow us to search for new physics inaccessible with other means by leveraging specialized radiation detectors. Machine learning provides a new tool to maximize the information provided by these detectors. The information is sparse, which forces these algorithms to start from the lowest level data and design customized models to produce results. The focus of this seminar...

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