114 citations · 427 across the 17 of their papers we have counts for
17 papers
2022 Review of Data-Driven Plasma Science
Rushil Anirudh, Rick Archibald, M. Salman Asif +60
Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data…
The data-driven future of high energy density physics
Peter W. Hatfield, Jim A. Gaffney, Gemma J. Anderson +20
The study of plasma physics under conditions of extreme temperatures, densities and electromagnetic field strengths is significant for our understanding of astrophysics, nuclear fu…
Experiments conducted in the burning plasma regime with inertial fusion implosions
J. S. Ross, J. E. Ralph, A. B. Zylstra +149
An experimental program is currently underway at the National Ignition Facility (NIF) to compress deuterium and tritium (DT) fuel to densities and temperatures sufficient to achiev…
Suppressing simulation bias using multi-modal data
Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears +6
Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with s…
Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations
Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears +3
Large-scale numerical simulations are used across many scientific disciplines to facilitate experimental development and provide insights into underlying physical processes, but th…
Benchmarking boron carbide equation of state using computation and experiment
Shuai Zhang, Michelle C. Marshall, Lin H. Yang +13
Boron carbide (BC) is of both fundamental scientific and practical interest in inertial confinement fusion (ICF) and high energy density physics experiments. We report the resu…
Comparison of ablators for the polar direct drive exploding pusher platform
Heather D. Whitley, G. Elijah Kemp, Charles Yeamans +36
We examine the performance of pure boron, boron carbide, high density carbon, and boron nitride ablators in the polar direct drive exploding pusher (PDXP) platform. The platform us…
Simultaneous compression and opacity data from time-series radiography with a Lagrangian marker
Damian C. Swift, Andrea L. Kritcher, James A. Hawreliak +12
Time-resolved radiography can be used to obtain absolute shock Hugoniot states by simultaneously measuring at least two mechanical parameters of the shock, and this technique is pa…
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models
Jayaraman J. Thiagarajan, Bindya Venkatesh, Rushil Anirudh +4
Predictive models that accurately emulate complex scientific processes can achieve exponential speed-ups over numerical simulators or experiments, and at the same time provide surr…
Enabling Machine Learning-Ready HPC Ensembles with Merlin
J. Luc Peterson, Ben Bay, Joe Koning +17
With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensembl…
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets
Sam Ade Jacobs, Brian Van Essen, David Hysom +11
Training deep neural networks on large scientific data is a challenging task that requires enormous compute power, especially if no pre-trained models exist to initialize the proce…
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
Shusen Liu, Di Wang, Dan Maljovec +13
With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First…
Equation of state of warm-dense boron nitride combining computation, modeling, and experiment
Shuai Zhang, Amy Lazicki, Burkhard Militzer +18
The equation of state (EOS) of materials at warm dense conditions poses significant challenges to both theory and experiment. We report a combined computational, modeling, and expe…
Theoretical and experimental investigation of the equation of state of boron plasmas
Shuai Zhang, Burkhard Militzer, Michelle C. Gregor +11
We report a theoretical equation of state (EOS) table for boron across a wide range of temperatures (5.110-5.210 K) and densities (0.25-49 g/cm), and ex…
Observation and control of shock waves in individual nanoplasmas
Daniel D. Hickstein, Franklin Dollar, Jim A. Gaffney +11
In a novel experiment that images the momentum distribution of individual, isolated 100-nm-scale plasmas, we make the first experimental observation of shock waves in nanoplasmas.…
Bayesian inference of inaccuracies in radiation transport physics from inertial confinement fusion experiments
Jim A Gaffney, Dan Clark, Vijay Sonnad +1
First principles microphysics models are essential to the design and analysis of high energy density physics experiments. Using experimental data to investigate the underlying phys…
Bayesian Analysis of Inertial Confinement Fusion Experiments at the National Ignition Facility
J. A. Gaffney, D. Clark, V. Sonnad +1
We develop a Bayesian inference method that allows the efficient determination of several interesting parameters from complicated high-energy-density experiments performed on the N…