论文标题
粒子加速器的高级控制方法（ACM4PA）2019研讨会报告
Advanced Control Methods for Particle Accelerators (ACM4PA) 2019 Workshop Report
论文作者
论文摘要
Los Alamos目前正在开发新型的粒子加速器控制和诊断算法，以使具有比目前可能更低的束损耗的更高质量的光束。 The purpose of this workshop was to consider tuning and optimization challenges of a wide range of particle accelerators including linear proton accelerators such as the Los Alamos Neutron Science Center (LANSCE), rings such as the Advanced Photon Source (APS) synchrotron, free electron lasers (FEL) such as the Linac Coherent Light Source (LCLS) and LCLS-II, the European X-ray Free Electron Laser （Euxfel），瑞士FEL和计划中的玛丽·费尔（Marie Fel）以及等离子体唤醒场加速器，例如Facet，Facet-II和Cern醒来。一个主要的挑战是能够快速创建非常高质量，非常强烈，自定义的电流和能量轮廓光束，同时使用有限的实时非侵入性诊断，并利用时间变化的不确定的不确定的初始光束分布和加速器组件。目前，一些单独的加速器实验室一直在开发和应用自己的诊断工具以及自定义控制和ML算法以进行自动化机器调整和优化。该研讨会的目的是将一组加速器物理学家和相关控制器和ML专家汇集在一起，以定义哪些控制和诊断对现有和未来的加速器最有用，并为制定一个可以由社区共享和维持的新算法家族的计划。
Los Alamos is currently developing novel particle accelerator controls and diagnostics algorithms to enable higher quality beams with lower beam losses than is currently possible. The purpose of this workshop was to consider tuning and optimization challenges of a wide range of particle accelerators including linear proton accelerators such as the Los Alamos Neutron Science Center (LANSCE), rings such as the Advanced Photon Source (APS) synchrotron, free electron lasers (FEL) such as the Linac Coherent Light Source (LCLS) and LCLS-II, the European X-ray Free Electron Laser (EuXFEL), the Swiss FEL, and the planned MaRIE FEL, and plasma wake-field accelerators such as FACET, FACET-II, and AWAKE at CERN. One major challenge is an the ability to quickly create very high quality, extremely intense, custom current and energy profile beams while working with limited real time non-invasive diagnostics and utilizing time-varying uncertain initial beam distributions and accelerator components. Currently, a few individual accelerator labs have been developing and applying their own diagnostics tools and custom control and ML algorithms for automated machine tuning and optimization. The goal of this workshop was to bring together a group of accelerator physicists and accelerator related control and ML experts in order to define which controls and diagnostics would be most useful for existing and future accelerators and to create a plan for developing a new family of algorithms that can be shared and maintained by the community.
