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Bremsstrahlung Denoising Software for X-ray Data Using Equivariant Neural Networks

Starke, Sebastian; Šmíd, Michal; Steinbach, Peter

Large ammount of energetic bremstrahlung is created in experiments where ultra high intensity laser interacts with solid targets. This constitutes a distinct background signal on detectors used in the experiment. Such background then can obscure the desired measured signal. We provide a tool which can distinguish this background from the useful signal. The first and prominent case where this was utilized is in the detection of Small angle x-ray scattering (SAXS) diagnostics at the HED instrument at European XFEL, but we believe this tool could find much broader usage.

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