标题： PSI muEDM实验中束流注入和存储的贝叶斯优化 显示英文标题

标题： Bayesian optimization of beam injection and storage in the PSI muEDM Experiment

摘要： 保罗·谢勒研究所的muEDM实验旨在以前所未有的灵敏度$6 \times 10^{-23}\,\mathrm{e}\cdot\mathrm{cm}$测量电偶极矩。 该实验的关键方面之一是注入和储存μ介子束流，该束流穿过一个长而窄的超导通道后进入螺线管磁铁。 然后，μ介子被脉冲磁场偏转到螺线管中心区域内的稳定轨道上，在此测量电偶极矩。 为了研究束流注入和储存过程，我们开发了一个G4beamline模拟来建模束流注入和储存的动力学，并结合了所有相关的电场和磁场。 随后，我们采用了贝叶斯优化技术来提高muEDM实验第一阶段的μ介子存储效率。 优化是通过G4beamline模拟的数据展示的。 我们观察到束流注入和储存效率有所提高，在使用高斯过程的贝叶斯优化下达到0.556%，而使用多项式混沌展开时为0.324%。 这种方法可以应用于调整实际实验参数，帮助实现muEDM实验中束流注入和储存所需的性能。 显示英文摘要

摘要： The muEDM experiment at the Paul Scherrer Institute aims to measure the electric dipole moment with an unprecedented sensitivity of $6 \times 10^{-23}\,\mathrm{e}\cdot\mathrm{cm}$. A key aspect of this experiment is the injection and storage of the muon beam, which traverses a long, narrow superconducting channel before entering a solenoid magnet. The muon is then kicked by a pulsed magnetic field into a stable orbit within the solenoid's central region, where the electric dipole moment is measured. To study the beam injection and storage process, we developed a G4beamline simulation to model the dynamics of beam injection and storage, incorporating all relevant electric and magnetic fields. We subsequently employed a Bayesian optimization technique to improve the muon storage efficiency for Phase I of the muEDM experiment. The optimization is demonstrated using data simulated by G4beamline. We have observed an enhancement in the beam injection and storage efficiency, which increased to 0.556\% through the utilization of Bayesian optimization with Gaussian processes, compared to 0.324\% when employing the polynomial chaos expansion. This approach can be applied to adjust actual experimental parameters, aiding in achieving the desired performance for beam injection and storage in the muEDM experiment.