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High-repetition-rate diagnostics and analysis techniques for HED experiments

POSTER

Abstract

As the number and capability of high-repetition-rate (HRR), high-intensity lasers generating data for the high-energy-density (HED) science community increases, so too must our diagnostic and analytic capabilities. Demonstrating the robustness of HRR-capable diagnostics and fast, robust analysis tools which can deliver high-quality outputs in real time, initially during burst mode operations but eventually continuously, will enable the development of a fully integrated system which can run at the maximum repetition rate of the host facility. We present progress in converting single-shot optical, neutron, charged particle and x-ray diagnostics to HRR operation, and the application of machine learning and physics-based system models to accelerate data analysis. These are important steps towards realizing autonomous active feedback control of the widest possible range of HRR HED experiments.

Presenters

  • Matthew P Hill

    Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

Authors

  • Matthew P Hill

    Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

  • Blagoje Z Djordjevic

    Lawrence Livermore Natl Lab

  • Eric Folsom

    LLNL

  • Elizabeth S Grace

    Lawrence Livermore National Laboratory

  • Derek Mariscal

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Anna Murphy

    Lawrence Livermore National Laboratory, LLNL

  • Dean R Rusby

    Lawrence Livermore National Lab, Lawrence Livermore National Laboratory

  • Graeme G Scott

    Lawrence Livermore National Laboratory

  • Matthew P Selwood

    Lawrence Livermore Natl Lab

  • Raspberry Simpson

    Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

  • Kelly K Swanson

    Lawrence Livermore National Laboratory

  • Franziska S Treffert

    Lawrence Livermore National Laboratory, SLAC National Accelerator Laboratory

  • Jackson G Williams

    Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

  • Warren L York

    Lawrence Livermore National Laboratory

  • Ghassan Zeraouli

    Colorado State University, Lawrence Livermore National Laboratory, Colorado State University

  • Tammy Ma

    Lawrence Livermore Natl Lab