  The SEparator for CApture Reactions (SECAR) is a next-generation recoil
separator system at the Facility for Rare Isotope Beams (FRIB) designed for the
direct measurement of capture reactions on unstable nuclei in inverse
kinematics. To maximize the performance of this system, stringent requirements
on the beam alignment to the central beam axis and on the ion-optical settings
need to be achieved. These can be difficult to attain through manual tuning by
human operators without potentially leaving the system in a sub-optimal and
irreproducible state. In this work, we present the first development of online
Bayesian optimization with a Gaussian process model to tune an ion beam through
a nuclear astrophysics recoil separator. We show that this method achieves
small incoming angular deviations (\textless 1 mrad) in an efficient and
reproducible manner that is at least three times faster than standard
hand-tuning. Additionally, we present a Bayesian method for experimental
optimization of the ion optics, and show that it validates the nominal
theoretical ion-optical settings of the device, and improves the mass
separation by 32\% for some beams.
