The CARIBU-matic project: automation for the transport of radioactive beams from the CARIBU source

The CARIBU source at the ATLAS user facility provides beams of radioactive isotopes made from the spontaneuos fission of a 252Cf source. Such radioactive beams allow our users to carry out their cutting-edge experiments. However, the stardard approach at extracting and transporting the beams to the user's end stations is based on time-consuming expert-driven manual tuning methods. In this talk, we will give an update on the CARIBU-matic project, which is an effort to automate components of the radioactive beam delivery process through machine-learning methods and hardware improvements. Results from an early implementation of the automation of CARIBU beam transport via Bayesian optimization, using Xopt [1] and Badger [2], will be presented.

[1] R. Roussel., et al., "Xopt: A simplified framework for optimization of accelerator problems using advanced algorithms", in Proc. IPAC'23, Venezia.doi:https://doi.org/10.18429/JACoW-14th International Particle Accelerator Conference-THPL164

[2] Zhang, Z., et al. "Badger: The missing optimizer in ACR", in Proc. IPAC'22, Bangkok. doi:10.18429/JACoW-IPAC2022-TUPOST058