Particle accelerators are extremely complex machines that are challenging to simulate, design, and control. Over the past decade, artificial intelligence (AI) and machine learning (ML) techniques have made dramatic advancements across various scientific and industrial domains, and rapid improvements have been made in the availability and power of computing resources. These developments have begun to revolutionize the way particle accelerators are designed and controlled, and AI/ML techniques are beginning to be incorporated into regular operations for accelerators. This article provides a high-level overview of the history of AI/ML in accelerators and highlights current developments along with contrasting discussion about traditional methods for accelerator design and control. Areas of current technological challenges in developing reliable AI/ML methods are also discussed along with future research directions.

中文翻译：

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用于粒子加速器设计和控制的机器学习：回顾和展望未来


粒子加速器是极其复杂的机器，在仿真、设计和控制方面具有挑战性。在过去十年中，人工智能 （AI） 和机器学习 （ML） 技术在各个科学和工业领域取得了巨大进步，计算资源的可用性和能力也得到了快速改进。这些发展已经开始彻底改变粒子加速器的设计和控制方式，AI/ML 技术开始被纳入加速器的常规操作中。本文简要概述了加速器中 AI/ML 的历史，重点介绍了当前的发展情况，并对加速器设计和控制的传统方法进行了对比讨论。还讨论了开发可靠的 AI/ML 方法的当前技术挑战领域以及未来的研究方向。