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Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning – CORRIGENDUM 被引量:1
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作者 j.goodman M.King +3 位作者 E.J.Dolier R.Wilson R.J.Gray P.McKenna 《High Power Laser Science and Engineering》 SCIE CAS CSCD 2024年第1期116-116,共1页
Due to an isolated error in the 3D simulation parameters,the laser energy and intensity(calculated using the energy)values were incorrectly stated as 10.9 J and 3×10^(22) W cm^(−2),respectively,in Sections 3.3,7 ... Due to an isolated error in the 3D simulation parameters,the laser energy and intensity(calculated using the energy)values were incorrectly stated as 10.9 J and 3×10^(22) W cm^(−2),respectively,in Sections 3.3,7 and 8.The correct values are 39.8 J and 1.1×10^(23) W cm^(−2).Similarly,the values stated for the higher energy case,109 J and 3×10^(23) W cm^(−2) in Section 7,should be 398 J and 1.1×10^(24) W cm^(−2),respectively. 展开更多
关键词 Bayesian optimization gamma rays laser-solid interactions machine learning radiation reaction
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Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning 被引量:3
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作者 j.goodman M.King +3 位作者 E.J.Dolier R.Wilson R.J.Gray P.McKenna 《High Power Laser Science and Engineering》 SCIE EI CAS CSCD 2023年第3期15-31,共17页
The optimum parameters for the generation of synchrotron radiation in ultraintense laser pulse interactions with planar foils are investigated with the application of Bayesian optimization,via Gaussian process regress... The optimum parameters for the generation of synchrotron radiation in ultraintense laser pulse interactions with planar foils are investigated with the application of Bayesian optimization,via Gaussian process regression,to 2D particle-incell simulations.Individual properties of the synchrotron emission,such as the yield,are maximized,and simultaneous mitigation of bremsstrahlung emission is achieved with multi-variate objective functions.The angle-of-incidence of the laser pulse onto the target is shown to strongly influence the synchrotron yield and angular profile,with oblique incidence producing the optimal results.This is further explored in 3D simulations,in which additional control of the spatial profile of synchrotron emission is demonstrated by varying the polarization of the laser light.The results demonstrate the utility of applying a machine learning-based optimization approach and provide new insights into the physics of radiation generation in laser-foil interactions,which will inform the design of experiments in the quantum electrodynamics(QED)-plasma regime. 展开更多
关键词 Bayesian optimization gamma rays laser-solid interactions machine learning radiation reaction
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