上海科技大学知识管理系统

In this paper, the parallel Bayesian optimization algorithm is investigated for the simulation optimization of compact free electron lasers (FELs) driven by laser wakefield accelerators (LWFAs). The radiation energy serves as the objective function, which can be optimized to 25 mu J after several tens of iterations, initiating from random input samplings in soft x-ray regimes. The analysis of the FEL gain process has revealed that the localized properties of the electron beam (e beam) can be concurrently optimized, ensuring a high efficiency of energy extraction from the e beam. Our proposed scheme not only presents a viable design for compact FELs driven by LWFAs in the soft x-ray regime utilizing the start-to-end model, but also highlights the great potential of parallel Bayesian optimization algorithms for tackling the challenges associated with costly and complex black-box optimization problems.