Automation of Inertial Fusion Target Design with Python

The process of tuning an inertial confinement fusion pulse shape to a specific target design is highly iterative process. When done manually, each iteration has large latency and is consequently time consuming. We have developed several techniques that can be used to automate much of the pulse tuning process and significantly accelerate the tuning process by removing the human induced latency. The automated data analysis techniques require specialized diagnostics to run within the simulation. To facilitate these techniques, we have embedded a loosely coupled Python interpreter within a pre-existing radiation-hydrodynamics code, Hydra. To automate the tuning process we use numerical optimization techniques and construct objective functions to identify