APS Logo

Accelerating the rate of discovery: Toward high-repetition-rate HED science

ORAL

Abstract

As high-intensity short-pulse lasers that can operate at high-repetition-rate (HRR) (>10 Hz) come online around the world, the high-energy-density (HED) science they enable will experience a radical paradigm shift. The >1000x increase in shot rate over today’s shot-per-hour drivers translates into dramatically faster data acquisition and more experiments, and thus the potential to significantly accelerate the advancement of HED science. 

 

Current energetic driver facilities depend on the ability to manually tune the lasers, the targets, the diagnostics settings, and more, between single shots or sets of shots through a manual feedback loop of data collection, data analysis, and optimization largely driven by experience and intuition. At 10 Hz, this paradigm is no longer sustainable as more complex data is collected more quickly than is possible to analyze manually.

 

Fully realizing the potential benefits of HRR facilities requires a fundamental shift in the design and execution of experiments done on them, the development of supporting technologies such as high-throughput targetry and diagnostics, and the evolution of machine learning techniques to couple traditional scientific computing with advanced data analytics. On-the-fly optimization of experiments will become ever more crucial as higher repetition rates will lead to more deliberate inter-shot variations and the improved operational range to allow exploration over larger regions of phase space. 

 

We will present the vision and ongoing work to realize a HRR framework for rapidly delivered optimized experiments coupled to cognitive simulation to provide new insights in HED science.

–

Presenters

  • Tammy Ma

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

Authors

  • Tammy Ma

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Derek Mariscal

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • MariAnn Albrecht

    Lawrence Livermore National Laboratory

  • Rushil Anirudh

    LLNL, Lawrence Livermore National Laboratory

  • Peer-Timo Bremer

    Lawrence Livermore National Laboratory

  • Blagoje Djordjevic

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Scott Feister

    California State University, Channel Isl, Department of Computer Science, California State University Channel Islands, Camarillo, California 93120, USA, California State University Channel Islands

  • Thomas Galvin

    Lawrence Livermore National Laboratory

  • Elizabeth S Grace

    Georgia Institute of Technology

  • Sandrine Herriot

    Lawrence Livermore National Laboratory

  • Sam A Jacobs

    Lawrence Livermore National Laboratory

  • Bhavya Kailkhura

    Lawrence Livermore National Laboratory

  • Andreas J Kemp

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Reed C Hollinger

    Colorado State University, Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80521 USA

  • Joohwan Kim

    University of California, San Diego

  • Shusen Liu

    Lawrence Livermore National Laboratory

  • Joshua Ludwig

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Jorge J Rocca

    Colorado State University, Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80521 USA

  • Graeme G Scott

    Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

  • Raspberry A Simpson

    Massachusetts Institute of Technology MI, Massachusetts Institute of Technology

  • Brian K Spears

    Lawrence Livermore Natl Lab

  • Thomas Spinka

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Kelly Swanson

    Lawrence Livermore National Laboratory

  • Vincent Tang

    Lawrence Livermore National Laboratory

  • Jayaraman J Thiagarajan

    LLNL, Lawrence Livermore National Laboratory

  • Brian Van Essen

    Lawrence Livermore National Laboratory

  • Shoujun Wang

    Colorado State University, Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80521 USA

  • Scott Wilks

    LLNL, Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Jackson J Williams

    Lawrence Livermore Natl Lab, Lawrence Livermore National Lab, Lawrence Livermore National Laboratory

  • Ghassan Zeraouli

    Colorado State University

  • Jize Zhang

    Lawrence Livermore National Laboratory

  • Mark C Herrmann

    Lawrence Livermore National Lab, Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

  • Constantin Haefner

    Fraunhofer Institute for Laser Technology