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arXiv 2601.09574physics.acc-ph
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基于方阵的六维收敛图法用于非线性束流动力学分析

Square matrix-based six-dimensional convergence map for nonlinear beam dynamics analysis

Institute of High Energy Physics, Chinese Academy of Sciences(中国科学院高能物理研究所);University of the Chinese Academy of Sciences(中国科学院大学);Facility for Rare Isotope Beams, Michigan State University(密歇根州立大学稀有同位素束流设施)

Jinyu Wan, Yue Hao

AI总结:

本文提出一种基于方阵的六维收敛图法,用于非线性束流动力学分析,有效解析高阶共振结构并应用于电子离子对撞机的动态开口研究。

摘要:

基于方阵的收敛图(CM)方法已在几个4维动力系统中证明了其在刻画非线性动力学方面的有效性。然而,当存在时间依赖的扰动,如对撞机中的蟹式 kicks 时,进行全面的6维分析变得至关重要,以准确捕捉横向和纵向运动之间的耦合。在本工作中,我们通过采用基于特征分解的方阵公式结合迭代过程,将CM方法扩展到完整的6维相空间。所提出的6维CM方法首先使用简化的蟹式图进行验证。我们证明了6维CM通过仅使用一-turn图保持了计算效率,同时成功解析了传统频率图分析(FMA)无法解析的高阶共振结构。该方法随后应用于未来电子离子对撞机(EIC)的动态开口(DA)研究。CM分析所得结果与FMA得出的结果表现出高度一致,证明其作为非线性束流动力学分析和DA评估的强大工具的潜力,以及在其他非线性动力学系统中的广泛应用前景。

英文摘要:

The square matrix-based convergence map (CM) method has proven effective in characterizing nonlinear dynamics in several 4-D dynamical systems. However, when time-dependent perturbations, such as crabbing kicks in colliders, are present, a comprehensive 6-D analysis becomes essential to accurately capture the coupling between transverse and longitudinal motions. In this work, we extend the CM method to the full 6-D phase space by employing an eigen-decomposition-based formulation of the square matrix combined with iterative procedures. The proposed 6-D CM approach is first validated using a simplified crabbing map. We demonstrate that the 6-D CM preserves computational efficiency by using only one-turn map, while successfully resolving high-order resonance structures that remain unresolved by conventional frequency map analysis (FMA). This method is subsequently applied to the dynamic aperture (DA) study of the future Electron-Ion Collider (EIC). The results obtained from the CM analysis exhibit close agreement with those derived from FMA, demonstrating its potential as a powerful tool for nonlinear beam dynamics analysis and DA evaluation, as well as for broader applications in other nonlinear dynamical systems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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