Machine learning drives "autonomous" control of particle accelerators
Researchers are using machine learning to enable autonomous control of particle accelerators, opening up new possibilities for commissioning and operating high-power accelerators. The technology has been successfully applied to the CAFe2 superconducting segment, achieving global trajectory adaptive control.