Maximizing Number of Protons in Fusion Process Using Machine Learning

In the goal of working towards more efficient fusion ignition processes by maximizing the number of protons produced, a neural network (NN) was trained on experimental data obtained from BELLA iP2 laser facility. The NN parameters have currently been optimized to fit the data. The next goal will be to train the NN on both experimental and simulation data, while retaining the correlation, to avoid the necessity of a time consuming experimental campaign at all inputs parameters. This NN will be used to determine the operating parameters that will produce the most protons at a given energy range.