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Department of Physics and Astronomy
University of Mississippi


Event Information:

  • Tue

    Seminar: Neutrino Physics with Deep Learning: Applications, Successes, and Lessons

    4:00 pmLewis Hall 101

    Fernanda Psihas
    Neutrino Division
    Fermi National Accelerator Laboratory

    Neutrino Physics with Deep Learning: Applications, Successes, and Lessons

    Neutrino experiments study the least understood of the Standard Model particles by observing their direct interactions with matter or searching for ultra-rare signals. The study of neutrinos typically requires overcoming large backgrounds, elusive signals, and small statistics. The introduction of state-of-the-art machine learning tools to solve analysis tasks has made major impacts to these challenges in neutrino experiments across the board. Machine learning algorithms have become an integral tool of neutrino physics, and their development is of great importance to the capabilities of next generation experiments. An understanding of the roadblocks, both human and computational, and the challenges that still exist in the application of these techniques is critical to their proper and beneficial utilization for physics applications. Dr. Psihas will showcase applications to detector data analysis developed in the past few years and present the current status of machine learning applications for neutrino physics in terms of the challenges and opportunities that are at the intersection between these two fields.

    There will be refreshments at 3:45 pm in Lewis 104.