JuTrack：一个用于自动可微加速器建模与粒子追踪的Julia包
JuTrack: a Julia package for auto-differentiable accelerator modeling and particle tracking
AI总结：
本文提出Julia语言开发的加速器建模包JuTrack，结合编译器级自动微分实现快速导数计算，有效支持敏感性分析与优化任务，并在空间电荷发射度增长、非线性束流动力学及EIC格点调谐等应用中验证了其有效性。
摘要：
高效的加速器建模与粒子追踪是现代粒子加速器设计与配置的关键。本文提出了JuTrack，这是一个用Julia语言开发的嵌套加速器建模包，并增强了编译器级别的自动微分（AD）。借助AD，JuTrack能够在加速器建模中实现快速导数计算，从而促进敏感性分析和优化任务。我们通过多项实际应用展示了AD导出导数的有效性，包括空间电荷引起的发射度增长的敏感性分析、同步辐射光源的非线性束流动力学分析，以及未来电子-离子对撞机（EIC）的格点参数调谐。通过引入自动微分，该包为加速器物理学家在束流物理研究和加速器设计优化方面开辟了新的可能性。
英文摘要：
Efficient accelerator modeling and particle tracking are key for the design and configuration of modern particle accelerators. In this work, we present JuTrack, a nested accelerator modeling package developed in the Julia programming language and enhanced with compiler-level automatic differentiation (AD). With the aid of AD, JuTrack enables rapid derivative calculations in accelerator modeling, facilitating sensitivity analyses and optimization tasks. We demonstrate the effectiveness of AD-derived derivatives through several practical applications, including sensitivity analysis of space-charge-induced emittance growth, nonlinear beam dynamics analysis for a synchrotron light source, and lattice parameter tuning of the future Electron-Ion Collider (EIC). Through the incorporation of automatic differentiation, this package opens up new possibilities for accelerator physicists in beam physics studies and accelerator design optimization.
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