Using Artificial Intelligence in Cyclotron Design

In cyclotron development, a large number of calculations are required for both individual accelerator systems and particle motion dynamics. Artificial intelligence (AI) can contribute to increasing the speed of calculations, optimizing the codes, and improving the quality of the results. The initial results of using machine learning (ML) for magnetic field formation are presented, and the potential applications of computer vision and AI prospects for optimizing beam motion are analyzed.

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Publication Details

Journal
Physics of Particles and Nuclei Letters
Published
2025-08-01
DOI
https://doi.org/10.1134/s1547477125700396
Primary Topic
Plasma Diagnostics and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Using Artificial Intelligence in Cyclotron Design

I. D. Lyapin, Oleg Karamyshev, Taisia Karamysheva, M. A. Shuravin
Physics of Particles and Nuclei Letters
Plasma Diagnostics and Applications
article

Using Artificial Intelligence in Cyclotron Design

I. D. Lyapin, Oleg Karamyshev, Taisia Karamysheva, M. A. Shuravin
article en

Abstract

In cyclotron development, a large number of calculations are required for both individual accelerator systems and particle motion dynamics. Artificial intelligence (AI) can contribute to increasing the speed of calculations, optimizing the codes, and improving the quality of the results. The initial results of using machine learning (ML) for magnetic field formation are presented, and the potential applications of computer vision and AI prospects for optimizing beam motion are analyzed.

Physics of Particles and Nuclei LettersVol. 22(4)
Joint Institute for Nuclear Research (RU)
Openalex Percentile: Top 81%
Plasma Diagnostics and Applications
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