用归一化流研究电子束团沿FEL光束线的分布
Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows
摘要：
对激光驱动的自由电子激光的理解和控制一直是一个需要深入实验和理论研究的难题。模拟和实验收集的数据之间的差距可能会使研究和解释所获得的结果复杂化。在这项工作中，我们开发了一个基于深度学习的代理，可以帮助填补这一空白。本文介绍了一种基于归一化流的代理模型，用于自由电子激光束线中电子云的条件相空间表示。实现的结果，让我们讨论进一步的好处和限制，利用模型，以获得更深入的了解光束线内的基本过程。
英文摘要：
Understanding and control of Laser-driven Free Electron Lasers remain to be difficult problems that require highly intensive experimental and theoretical research. The gap between simulated and experimentally collected data might complicate studies and interpretation of obtained results. In this work we developed a deep learning based surrogate that could help to fill in this gap. We introduce a surrogate model based on normalising flows for conditional phase-space representation of electron clouds in a FEL beamline. Achieved results let us discuss further benefits and limitations in exploitability of the models to gain deeper understanding of fundamental processes within a beamline.
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。
