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• W4288045119 endingPage "128814" @default.
• W4288045119 startingPage "128814" @default.
• W4288045119 abstract "The flattop (FT) beam, one important laser beam, is often applied to the high-power fiber laser. It is preferred to generate the FT beam by M-type fiber. However, the design of optical fiber structure is complex and time-consuming. In this work, based on the M-type fiber, a machine learning method using artificial neural network (ANN) is proposed to inversely design the FT beam fiber. By using this trained ANN, the inverse design of the FT beam fiber is realized, according to the performances of FT beam, the structural parameters of M-type fiber are determined. In addition, the influence of structural parameters on the performances of FT beam, including the flatness, the power confining factor and the effective area, are discussed in detail. The proposed ANN-based machine learning method provides an efficient, accurate prediction for FT beam fiber with excellent performances." @default.
• W4288045119 created "2022-07-27" @default.
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• W4288045119 date "2022-12-01" @default.
• W4288045119 modified "2023-10-16" @default.
• W4288045119 title "Machine learning aided inverse design for flattop beam fiber" @default.
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• W4288045119 doi "https://doi.org/10.1016/j.optcom.2022.128814" @default.
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