Nuclear Theory IV

ORAL · L17 · ID: 2651031

Presentations

  • Uncertainty quantification in (p,n) reactions

    ORAL

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    Publication: A. J. Smith, C. Hebborn, F. M. Nunes, and R. G. T. Zegers, Uncertainty quantification in (p, n) reactions (2024), arXiv:2403.18629.

    Presenters

    • Andrew J Smith

      Michigan State University

    Authors

    • Andrew J Smith

      Michigan State University

    • Chloë Hebborn

      Michigan State University and Facility for Rare Isotope Beams

    • Filomena Nunes

      Michigan State University

    • Remco G.T. Zegers

      Michigan State University

    View abstract →

  • Unmasking the Underlying Correlations in Nuclear Reaction Cross Sections

    ORAL

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    Publication: Unmasking Correlations in Nuclear Cross Sections with Graph Neural Networks: arXiv:2404.02332
    Illuminating Systematic Trends in Nuclear Data with Generative Machine Learning Models: arXiv:2403.16389

    Presenters

    • Kyle A Wendt

      Lawrence Livermore National Laboratory

    Authors

    • Kyle A Wendt

      Lawrence Livermore National Laboratory

    • Sinjini Mitra

      Arizona State University

    • Hongjun Choi

      Lawrence Livermore National Laboratory

    • Shusen Liu

      Lawrence Livermore National Laboratory

    • Ruben Glatt

      Lawrence Livermore National Laboratory

    • Nicolas Schunck

      Lawrence Livermore National Laboratory

    • Xiao Chen

      Lawrence Livermore Natl Lab

    • Jordan Fox

      Argonne National Laboratory

    View abstract →

  • Coupled Channels Reduced Order Scattering Emulators

    ORAL

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    Presenters

    • Manuel Catacora-Rios

      MIchigan State University

    Authors

    • Manuel Catacora-Rios

      MIchigan State University

    • Filomena Nunes

      Michigan State University

    • Pablo G Giuliani

      Facility for Rare Isotopes Beams, Facility for Rare Isotope Beams

    • Richard J Furnstahl

      Ohio State University

    • Kyle S Godbey

      Michigan State University, FRIB, Michigan State University, Facility for Rare Isotope Beams

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  • Description of nuclear properties using Symbolic Machine Learning

    ORAL

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    Publication: Discovering Nuclear Models from Symbolic Machine Learning (https://arxiv.org/pdf/2404.11477)

    Presenters

    • Jose M Munoz

      MIT

    Authors

    • Jose M Munoz

      MIT

    • Ronald Fernando F Garcia Ruiz

      MIT Laboratory for Nuclear Science, Massachusetts Institute of Technology

    • Silviu-Marian M Udrescu

      Massachusetts Institute of Technology

    View abstract →