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Improved Bayesian optimization of laser-driven plasma surface high harmonic generation

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成果类型:
期刊论文
作者:
Lili Fan;Ziwei Wang;Chenfei Liao;Jingwei Wang*
通讯作者:
Jingwei Wang
作者机构:
[Lili Fan; Ziwei Wang; Chenfei Liao] School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China
[Jingwei Wang] State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
通讯机构:
[Jingwei Wang] S
State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
语种:
英文
关键词:
Absorption spectroscopy;Attosecond pulses;Deep learning;High harmonic generation;Laser system design;Neural networks
期刊:
Optics Express
ISSN:
1094-4087
年:
2025
卷:
33
期:
5
页码:
11254-11263
基金类别:
National Key Research and Development Program of China (2023YFA1406804, 2024YFA1612102); National Natural Science Foundation of China (11991074, 11871388); the International Partnership Program of the Chinese Academy of Sciences (111GJHZ2023060GC); Strategic Priority Research Program of the Chinese Academy of Sciences (XDA25051100, XDA25010100, XDB0890304); Natural Science Foundation of Wuhan (Chenguang Project) (2024040801020332); CAS Project for Young Scientists in Basic Research (YSBR-115).
机构署名:
本校为第一机构
院系归属:
数学与计算机学院
摘要:
Plasma surface high-order harmonics generation (SHHG) driven by intense laser pulses on plasma targets enables a high-quality extreme ultraviolet (EUV) source with high pulse energy and outstanding spatiotemporal coherence. Optimizing the performance of SHHG is important for its applications in single-shot imaging and EUV absorption spectroscopy. In this work, we demonstrate the optimization of laser-driven SHHG by an improved Bayesian strategy. A traditional Bayesian algorithm is first employed to optimize the SHHG intensity in a two-dimensional parameter space. Then, an improved Bayesian str...

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