Bulletin of the American Physical Society
60th Annual Meeting of the APS Division of Plasma Physics
Volume 63, Number 11
Monday–Friday, November 5–9, 2018; Portland, Oregon
Session YP11: Poster Session IX: The crossover between high-energy-density plasmas and ultracold neutral plasmas ; Supplemental; Post-Deadline Abstracts (9:30am-12:30pm)
Friday, November 9, 2018
OCC
Room: Exhibit Hall A1&A
Abstract ID: BAPS.2018.DPP.YP11.59
Abstract: YP11.00059 : The Bayesian Inference Engine (BIE): a computational statistical inference framework for deceleration-phase Rayleigh-Taylor instability studies*
Presenter:
Benjamin J Tobias
(Los Alamos National Laboratory)
Authors:
Benjamin J Tobias
(Los Alamos National Laboratory)
Sasikumar Palaniyappan
(Los Alamos National Laboratory)
Joshua Paul Sauppe
(Los Alamos National Laboratory)
Codie Yoshiko Fiedler Kawaguchi
(Los Alamos National Laboratory)
Kirk Flippo
(Los Alamos National Laboratory)
John L Kline
(Los Alamos National Laboratory)
The Bayesian Inference Enging (BIE) has been utilized for the analysis of radiographic images capturing the dynamic evolution of deceleration-phase R.-T. modes during laser-driven implosions of cylindrical targets at Omega. Within the BIE, an analyst may construct a parameterized physical model representing the object being imaged, produce synthetic data, and optimize model parameters to obtain a maximum a posteriori solution that considers both weighted statistical likelihood and prior information. 2D implosions are modeled so as to infer the growth rate and evolution of cylindrical modes in a driven Al marker layer, comprehensively accounting for blur, alignment and illumination effects to achieve unprecedented accuracy for comparison to hydrodynamic simulation. The BIE also allows uncertainties to be quantified in a rigorous manner through response surface methodologies, establishing sensible error bars and guiding the refinement of experimental techniques.
*This work is supported by the National Nuclear Security Administration, performed by Los Alamos National Laboratory, operated by Los Alamos National Security, LLC, under contract DE-AC52-06NA25396.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DPP.YP11.59
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