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A variety of spherical crystal x-ray imager (SCXI) diagnostics have beendeveloped and fielded on Magnetized Liner Inertial Fusion (MagLIF) experimentsat the Sandia National Laboratories Z-facility. These different imagingmodalities provide detailed insight into different physical phenomena such asmix of liner material into the hot fuel, cold liner emission, or reduce impactof liner opacity. However, several practical considerations ranging from thelack of a consistent spatial fiducial for registration to differentpoint-spread-functions and tuning crystals or using filters to highlightspecific spectral regions make it difficult to develop broadly applicablemetrics to compare experiments across our stagnation image database withoutmaking significant unverified assumptions. We leverage experimental data for amodel-free assessment of sensitivities to instrumentation-based features forany specified image metric. In particular, we utilize a database of historicaland recent MagLIF data including $N_{\text{scans}} = 139$ image plate scansgathered across $N_{\text{exp}} = 67$ different experiments to assess theimpact of a variety of features in the experimental observations arising fromuncertainties in registration as well as discrepancies in signal-to-noise ratioand instrument resolution. We choose a wavelet-based image metric known as theMallat Scattering Transform for the study and highlight how alternate metricchoices could also be studied. In particular, we demonstrate a capability tounderstand and mitigate the impact of signal-to-noise, image registration, andresolution difference between images. This is achieved by utilizing multiplescans of the same image plate, sampling random translations and rotations, andapplying instrument specific point-spread-functions found by ray tracing tohigh-resolution datasets, augmenting our data in an effectively model-freefashion.

A framework for experimental-data-driven assessment of Magnetized Liner Inertial Fusion stagnation image metrics