自导引激光尾场加速器的能量优化标度律
Energy-optimized scaling laws for self-guided laser wakefield accelerators
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中文总结 AI 辅助
本研究采用贝叶斯优化结合粒子模拟技术，推导出自导引激光尾场加速器的能量优化标度律，为设计高性能激光尾场加速实验提供实用指导。
中文摘要 AI 辅助
激光尾场加速技术有望为医学、工业及基础科学领域提供紧凑型电子加速器。尽管该领域已取得快速进展，但准确预测给定实验配置下可获得的电子能量及达到该能量所需的加速长度仍是一项未解决的挑战。本研究采用贝叶斯优化结合先进的粒子模拟技术，确定了由给定能量和波长的激光驱动的自导引激光尾场加速器所能产生的最大电子能量。通过在一系列激光能量和波长范围内系统优化加速器性能，研究人员推导得出能量优化标度律。这些标度律可在最短加速长度内产生最高电子能量，仅用激光能量和波长即可表达，并附带实现该标度所需的完整激光与等离子体参数集。所得标度律为设计处于基本性能极限的先进激光尾场加速实验提供了实用指导。
英文摘要
Laser wakefield acceleration promises compact electron accelerators for applications in medicine, industry, and fundamental science. Yet, despite rapid progress, accurately predicting the electron energy attainable in a given experimental configuration and the acceleration length required to reach it remains an open challenge. Here we use Bayesian optimization combined with advanced particle-in-cell simulation techniques to determine the maximum electron energy that a self-guided laser wakefield accelerator driven by a laser of a given energy and wavelength can produce. By systematically optimizing the accelerator performance across a range of laser energies and wavelengths, we derive energy-optimized scaling laws. These scaling laws yield the highest electron energy over the shortest acceleration length possible, are expressed solely in terms of laser energy and wavelength, and are accompanied by the complete set of laser and plasma parameters required to enable the scaling. The resulting scaling laws provide practical guidance for designing state-of-the-art laser wakefield acceleration experiments operating at their fundamental performance limits.
