AI-Assisted Transport of Radioactive Ion Beams

• URL: http://arxiv.org/abs/2504.06469v2
• Date: Thu, 17 Apr 2025 00:25:50 GMT
• Title: AI-Assisted Transport of Radioactive Ion Beams
• Authors: Sergio Lopez-Caceres, Daniel Santiago-Gonzalez,
• Abstract summary: We introduce a system that employs Artificial Intelligence (AI) to assist in the transport process of radioactive beams.<n>This AI-assisted approach can be extended to other radioactive beam facilities around the world to improve operational efficiency and enhance scientific output.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Beams of radioactive heavy ions allow researchers to study rare and unstable atomic nuclei, shedding light into the internal structure of exotic nuclei and on how chemical elements are formed in stars. However, the extraction and transport of radioactive beams rely on time-consuming expert-driven tuning methods, where hundreds of parameters are manually optimized. Here, we introduce a system that employs Artificial Intelligence (AI), specifically utilizing Bayesian Optimization, to assist in the transport process of radioactive beams. We apply our methodology to real-life scenarios showing advantages when compared with standard tuning methods. This AI-assisted approach can be extended to other radioactive beam facilities around the world to improve operational efficiency and enhance scientific output.

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