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  • Open Access

AI-assisted transport of radioactive ion beams

S. Lopez-Caceres* and D. Santiago-Gonzalez

  • *Contact author: slopezcaceres@anl.gov; slopezcaceres1@gmail.com
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Phys. Rev. Accel. Beams 28, 072802 – Published 23 July, 2025

DOI: https://doi.org/10.1103/bwxw-w9jc

Abstract

Beams of radioactive heavy ions allow researchers to study rare and unstable atomic nuclei, shedding light on 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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Phys. Rev. Accel. Beams 28, 072802– Published 23 July, 2025
  • Received 8 April 2025
  • Accepted 20 June 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

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