Bayesian inference of inaccuracies in radiation transport physics from inertial confinement fusion experiments
Jim A Gaffney, Dan Clark, Vijay Sonnad, Stephen B Libby

TL;DR
This paper introduces a Bayesian approach to infer inaccuracies in radiation transport physics from inertial confinement fusion experiments, accounting for complex models and experimental noise, but finds limited reconciliation of simulation and experimental discrepancies.
Contribution
It presents a novel Bayesian inference method incorporating experimental and prior uncertainties to evaluate microphysics models from fusion experiment data.
Findings
Evidence of inaccuracies in X-ray drive intensity calculations
Detection of errors in Ge L-shell absorption models
Modifications to radiation transport do not fully reconcile simulations with experiments
Abstract
First principles microphysics models are essential to the design and analysis of high energy density physics experiments. Using experimental data to investigate the underlying physics is also essential, particularly when simulations and experiments are not consistent with each other. This is a difficult task, due to the large number of physical models that play a role, and due to the complex (and as a result, noisy) nature of the experiments. This results in a large number of parameters that make any inference a daunting task; it is also very important to consistently treat both experimental and prior understanding of the problem. In this paper we present a Bayesian method that includes both these effects, and allows the inference of a set of modifiers which have been constructed to give information about microphysics models from experimental data. We pay particular attention to…
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