Reinforcement Learning Techniques for the Optimization of Target Polarization in Nuclear Physics Scattering Experiments

The operation of dynamically polarized targets in nuclear physics experiments relies on continuous tuning of the microwave frequency to compensate for radiation damage and evolving material properties, a task that is traditionally performed through manual trial-and-error by expert operators.