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• W4287310059 abstract "X-ray radiography is a technique frequently used to diagnose convergent high-energy-density (HED) systems, such as inertial confinement fusion implosion, and provides unique information that is not available through self-emission measurements. We investigate the scope and limits of that information using a radiography simulation combined with the Bayesian inference workflow. The accuracy of density reconstruction from simulated radiographs of spherical implosions driven with 27 kJ laser energy is assessed, including the increase or decrease in accuracy due to the addition of Lagrangian marker layers, Poisson noise, and improved prior information. This work is the first to present the full uncertainty distributions inferred from radiography analysis in HED systems and demonstrates the importance of constructing the full posterior probability density, as opposed to a point estimate, due to the modal structure of the likelihood surface introduced by typical experimental noise sources. This general methodology can be used both for robust analysis of radiographic data and for an improved design of radiography experiments by modeling the full experimental system." @default.
• W4287310059 created "2022-07-25" @default.
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• W4287310059 date "2022-07-01" @default.
• W4287310059 modified "2023-09-24" @default.
• W4287310059 title "Density reconstruction in convergent high-energy-density systems using x-ray radiography and Bayesian inference" @default.
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• W4287310059 doi "https://doi.org/10.1063/5.0094729" @default.
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