利用耦合PIC与蒙特卡罗模拟的激光尾波场加速优化钼-99生产的贝叶斯方法
Bayesian Optimization of Molybdenum-99 Production by Laser Wakefield Acceleration Using Coupled PIC and Monte Carlo Simulations
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中文总结 AI 辅助
该研究通过耦合PIC与MC模拟的贝叶斯优化，大幅提升了激光尾波场加速产生钼-99的产量，为核医学关键同位素生产提供了高效优化方案。
中文摘要 AI 辅助
本研究将贝叶斯优化应用于由激光电子加速的PIC模拟与轫致辐射诱发核反应的蒙特卡罗（MC）模拟构成的闭环，以最大化钼-99（核医学中最常用放射性药物亚稳态锝-99的前体）的产量。PIC与MC模拟计算密集，除缩短耗时外，将贝叶斯优化与两种模拟耦合，使99Mo产量较仅基于PIC模拟的优化闭环输出经MC模拟后验估计99Mo产量的先前研究提升了一个数量级。
英文摘要
This work applies Bayesian optimization to a loop composed of PIC simulations of laser electron acceleration and Monte Carlo (MC) simulations of bremsstrahlung-induced nuclear reactions, to maximize the production of molybdenum-99, the precursor of the most used radiopharmaceutical in nuclear medicine, metastable technetium-99. PIC and MC simulations are computationally intensive, and besides reducing the time spent, the Bayesian optimization coupling both simulations resulted in an improvement of an order of magnitude in the $^\text{99}$Mo yield over a previous work, in which the output of an optimization loop based solely on PIC simulations was used a posteriori to estimate $^{99}\mathrm{Mo}$ production through a MC simulation.
