Minisymposium: Applications of Advanced Statistics and Machine Learning Methods in Nuclear Physics III

Presentations

• Towards Automation for γ-Ray Spectroscopy

  ORAL

  Dec. 1, 2023, 2:00 PM – Dec. 1, 2023, 2:15 PM

  Presenters

  • Tamas A Budner

    Argonne National Laboratory

  Authors

  • Tamas A Budner

    Argonne National Laboratory

  • David Lenz

    Argonne National Laboratory

  • Michael P Carpenter

    Argonne National Laboratory

  • Sven Leyffer

    Argonne National Laboratory

  • Filip G Kondev

    Argonne National Laboratory

  • Amel Korichi

    Université Paris-Saclay, IJCLab, Argonne National Laboratory

  • Torben Lauritsen

    Argonne National Laboratory

  • Thomas F Lynn

    Argonne National Laboratory

  • Marco Siciliano

    ANL, Argonne National Laboratory

  View abstract →

• Machine learning based design optimization for the search of neutrinoless double-beta decay with LEGEND

  ORAL

  Dec. 1, 2023, 2:15 PM – Dec. 1, 2023, 2:30 PM

  Presenters

  • Ann-Kathrin Schuetz

    Lawrence Berkeley National Laboratory

  Authors

  • Ann-Kathrin Schuetz

    Lawrence Berkeley National Laboratory

  View abstract →

• Using Convolutional Neural Networks to Classify Scintillator Data

  ORAL

  Dec. 1, 2023, 2:30 PM – Dec. 1, 2023, 2:45 PM

  Presenters

  • Adam Hartley

    Michigan State University, FRIB

  Authors

  • Adam Hartley

    Michigan State University, FRIB

  • Sean N Liddick

    Michigan State University, FRIB, FRIB/NSCL, Facility for Rare Isotope Beams, Michigan State University, East Lansing, MI 48824, USA, FRIB/MSU

  • Geir Ulvik

    University of Oslo

  • Morten Hjorth-Jensen

    Michigan State University

  • Aaron Chester

    Michigan State University

  View abstract →

• CARIBU-matic and the MUSIC ML project: examples of machine-learning applications for beam tuning and experimental data analysis/classification

  ORAL

  Dec. 1, 2023, 2:45 PM – Dec. 1, 2023, 3:00 PM

  Publication: [1] K. Raghavan, M.L. Avila, P. Balaprakash, H. Jayatissa, D. Santiago-Gonzalez, "Classification of events from α-induced reactions in the MUSIC detector via statistical and ML methods", https://arxiv.org/abs/2204.03137

  Presenters

  • Daniel Santiago-Gonzalez

    Argonne National Laboratory

  Authors

  • Daniel Santiago-Gonzalez

    Argonne National Laboratory

  • Melina Avila

    Argonne National Laboratory

  • Prasanna Balaprakash

    Oak Ridge National Laboratory

  • Heshani Jayatissa

    Argonne National Laboratory, Los Alamos National Laboratory

  • Krishnan Raghavan

    Argonne National Laboratory

  • Nathan Callahan

    Argonne National Laboratory

  View abstract →

• Offline reinforcement learning for closed-loop control of the VENUS ion source

  ORAL

  Dec. 1, 2023, 3:00 PM – Dec. 1, 2023, 3:15 PM

  Presenters

  • Yue Shi Lai

    Lawrence Berkeley National Laboratory

  Authors

  • Yue Shi Lai

    Lawrence Berkeley National Laboratory

  View abstract →

• Atomic Masses with Machine Learning for the Astrophysical R-process

  ORAL

  Dec. 1, 2023, 3:15 PM – Dec. 1, 2023, 3:30 PM

  Presenters

  • Mengke Li

    Clemson University

  Authors

  • Mengke Li

    Clemson University

  • Trevor M Sprouse

    Los Alamos National Laboratory

  • Bradley S Meyer

    Clemson University

  • Matthew R Mumpower

    LANL

  View abstract →

• Machine learning assisted filtering approach for ion source optimization and control

  ORAL

  Dec. 1, 2023, 3:30 PM – Dec. 1, 2023, 3:45 PM

  Presenters

  • victor watson

    Lawrence Berkeley National Laboratory

  Authors

  • victor watson

    Lawrence Berkeley National Laboratory

  • Heather L Crawford

    Lawrence Berkeley National Laboratory

  • Marco Salathe

    Lawrence Berkeley National Laboratory

  • Damon Todd

    Lawrence Berkeley National Laboratory

  View abstract →

• Quantifying uncertainty of nuclear properties within machine learning frameworks

  ORAL

  Dec. 1, 2023, 3:45 PM – Dec. 1, 2023, 4:00 PM

  Presenters

  • Mengyao Huang

    Lawrence Livermore National Laboratory

  Authors

  • Mengyao Huang

    Lawrence Livermore National Laboratory

  • Kyle A Wendt

    Lawrence Livermore Natl Lab

  • Nicolas F Schunck

    Lawrence Livermore National Laboratory

  • Xiao Chen

    Lawrence Livermore National Laboratory

  View abstract →