Today's article comes from the journal of Machine Learning Science and Technology. The authors are Colen et al., from Old Dominion University, in Virginia. In this paper, they're building a new control module for a particle accelerator; one that can pick the gradient settings for hundreds of RF cavities in order to get the most ideal beam energy and operational profile out of the system.
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