人工智能在回旋加速器设计中的应用

IF 0.4 Q4 PHYSICS, PARTICLES & FIELDS

Physics of Particles and Nuclei Letters Pub Date : 2025-08-11 DOI:10.1134/S1547477125700396

O. V. Karamyshev, I. D. Lyapin, T. V. Karamysheva, M. A. Shuravin

{"title":"人工智能在回旋加速器设计中的应用","authors":"O. V. Karamyshev, I. D. Lyapin, T. V. Karamysheva, M. A. Shuravin","doi":"10.1134/S1547477125700396","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":730,"journal":{"name":"Physics of Particles and Nuclei Letters","volume":"22 4","pages":"690 - 698"},"PeriodicalIF":0.4000,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Artificial Intelligence in Cyclotron Design\",\"authors\":\"O. V. Karamyshev, I. D. Lyapin, T. V. Karamysheva, M. A. Shuravin\",\"doi\":\"10.1134/S1547477125700396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":730,\"journal\":{\"name\":\"Physics of Particles and Nuclei Letters\",\"volume\":\"22 4\",\"pages\":\"690 - 698\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2025-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physics of Particles and Nuclei Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1134/S1547477125700396\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHYSICS, PARTICLES & FIELDS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics of Particles and Nuclei Letters","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1134/S1547477125700396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, PARTICLES & FIELDS","Score":null,"Total":0}

引用次数: 0

摘要

在回旋加速器的发展中，需要对单个加速器系统和粒子运动动力学进行大量的计算。人工智能（AI）有助于提高计算速度，优化代码，提高结果的质量。介绍了利用机器学习（ML）进行磁场形成的初步结果，并分析了计算机视觉和人工智能在优化光束运动方面的潜在应用前景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Using Artificial Intelligence in Cyclotron Design

查看原文本刊更多论文

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Physics of Particles and Nuclei Letters PHYSICS, PARTICLES & FIELDS-

CiteScore

0.80

自引率

20.00%

发文量

108

期刊介绍： The journal Physics of Particles and Nuclei Letters, brief name Particles and Nuclei Letters, publishes the articles with results of the original theoretical, experimental, scientific-technical, methodological and applied research. Subject matter of articles covers: theoretical physics, elementary particle physics, relativistic nuclear physics, nuclear physics and related problems in other branches of physics, neutron physics, condensed matter physics, physics and engineering at low temperatures, physics and engineering of accelerators, physical experimental instruments and methods, physical computation experiments, applied research in these branches of physics and radiology, ecology and nuclear medicine.