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Conference on Science at the Sanford Underground Research Facility

May 11 – 13, 2022
South Dakota Mines
US/Mountain timezone
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Session

Advanced Data Analysis - Parallel

May 12, 2022, 4:20 PM
EEP 255 (SD Mines)

EEP 255

SD Mines

Conveners

Advanced Data Analysis - Parallel

  • Matthias Plum (South Dakota School of Mines and Technology)

Presentation materials

There are no materials yet.

  1. 46. Application of machine learning to find anomalous events in LZ data
    Chami Amarasinghe (University of Michigan)
    5/12/22, 4:20 PM
    Advanced Data Analysis
    Oral

    The LUX-ZEPLIN (LZ) experiment is a WIMP direct detection experiment using a dual-phase xenon time projection chamber with a 7 ton active volume, expecting science results in 2022. In a rare-event experiment such as LZ, it is important to identify events stemming from unexpected backgrounds, errors in reconstruction, and abnormalities in detector function. General-purpose, unsupervised anomaly...

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  2. 51. Bias Mitigation for the LUX-ZEPLIN (LZ) Experiment
    David Woodward (Penn State University)
    5/12/22, 4:40 PM
    Advanced Data Analysis
    Oral

    LUX-ZEPLIN (LZ) is a dark matter experiment located at the Sanford Underground Research Facility (SURF) in South Dakota. LZ is expected to explore new regimes of experimental sensitivity to a variety of dark matter candidates, notably Weakly Interacting Massive Particles (WIMPs). In pursuing new physics, it is important to ensure results are not influenced by biases towards achieving a...

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  3. 57. Automated Neutrino Interaction Reconstruction and Particle Classification using Machine Learning in DUNE
    Andrew Mogan (Co)
    5/12/22, 5:00 PM
    Advanced Data Analysis
    Oral

    The upcoming Deep Underground Neutrino Experiment (DUNE) will provide answers to longstanding questions in neutrino physics, including the ordering of neutrino masses and the value of the CP-violating phase, $\delta_{CP}$. Utilizing liquid argon time projection chamber (LArTPC) technology, DUNE will rely on automated reconstruction of neutrino interactions and classification of final-state...

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  4. 22. The Machine Learning Epochs of Neutrinoless Double Beta Decay
    Aobo Li (UNC Chapel Hill)
    5/12/22, 5:20 PM
    Advanced Data Analysis
    Oral

    Neutrinoless Double Beta Decay (0νββ) is one of the primary research interests in particle and nuclear physics. As we enter the era of artificial intelligence, machine learning has grown exponentially in almost all types of 0νββ detectors. Thanks to its end-to-end nature, machine learning algorithms can easily surpass traditional algorithms by maximally extracting information from detectors....

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  5. 81. Deep Learning Reconstruction in the NOvA Experiment
    Prof. Jianming Bian (University of California, Irvine)
    5/12/22, 5:40 PM
    Advanced Data Analysis
    Oral

    The NOvA experiment is a long-baseline accelerator neutrino experiment. It uses the upgraded NuMI beam from Fermilab and measures electron neutrino appearance and muon neutrino disappearance at its Far Detector in Ash River, Minnesota. NOvA is the first neutrino experiment that implemented convolutional neural networks in event reconstruction. NOvA is also developing new deep-learning...

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