DECLNMER UPGRADES TO THE LLNL FLASH X-RAY INDUCTION LINEAR ACCELERATOR (FXR)The FXR is an induction linear acceleratorused for flash radiography at the Lawrence Livtmnore National Laboratory's Site 300 Test Facility. The FXR was originally completedin 1982and has been in continuoususe as a radiographictool. At that time the FXR produceda 17MeV, 2.2 kA burst of electronsfor a duration of 65 ns.An upgrade of the FXR was recentl completed. The purpose of this upgrade was to improve the performanceof the FXl by increasing the energy of the electron injector from 1.2 MeV to 2.5 MeV and the beam current from 2.2 kA to 3 kA, improving the magnetictransport system by redesigningthe solenoidaltransport fms coils, reducing the rf coupling of the electron beam to the accelerator cells, and by adding additional beam d@OStiC&We will desmibethe injectur upgradesand pdbrmanc~as well as our effbrts to tune the acceleratorby~g beam corkscrew motion and the impact of Beam Breakup Instabilityon beam centroidmotionthroughoutthe beam line as the currentis increasedto 3 kA.

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ANARI is a new 3-D rendering API, an emerging Khronos standard that enables visualization applications to leverage the state-of-the-art rendering techniques across diverse hardware platforms and rendering engines. Visualization applications have historically embedded custom-written renderers to enable them to provide the necessary combination of features, performance, and visual fidelity required by their users. As computing power, rendering algorithms, dedicated rendering hardware acceleration operations, and associated low-level APIs have advanced, the effort and costs associated with maintaining renderers within visualization applications have risen dramatically. The rising cost and complexity associated with renderer development creates an undesirable barrier for visualization applications to be able to fully benefit from the latest rendering methods and hardware. ANARI directly addresses these challenges by providing a high-level, visualization-oriented API that abstracts low-level rendering algorithms and hardware acceleration details while providing easy and efficient access to diverse ANARI implementations, thereby enabling visualization applications to support the state-of-the-art rendering capabilities.