论文标题
贝叶斯优化激光 - 血浆加速器的辅助物理模型有助于
Bayesian optimization of laser-plasma accelerators assisted by reduced physical models
论文作者
论文摘要
粒子中的模拟是激光 - 血浆加速器建模和优化的最重要的工具之一，因为它们从第一原理中重现了物理学。但是，与之相关的高计算成本可以严重限制参数和设计优化研究的范围。在这里，我们表明，多任贝叶斯优化算法可用于通过合并廉价评估的降低物理模型的信息来减轻对此类高保真模拟的需求。在原理证明的研究中，通过使用Wake-T降低模拟模拟的较低模拟，该算法证明了速度的速度速度。这为在较大的参数空间中对激光 - 等离子加速器的成本效益优化开辟了道路，这是朝着满足未来应用的远光质量要求的重要一步。
Particle-in-cell simulations are among the most essential tools for the modeling and optimization of laser-plasma accelerators, since they reproduce the physics from first principles. However, the high computational cost associated with them can severely limit the scope of parameter and design optimization studies. Here, we show that a multitask Bayesian optimization algorithm can be used to mitigate the need for such high-fidelity simulations by incorporating information from inexpensive evaluations of reduced physical models. In a proof-of-principle study, where a high-fidelity optimization with FBPIC is assisted by reduced-model simulations with Wake-T, the algorithm demonstrates an order-of-magnitude speedup. This opens a path for the cost-effective optimization of laser-plasma accelerators in large parameter spaces, an important step towards fulfilling the high beam quality requirements of future applications.
