Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm
Abstract Ultrashort pulses, characterized by their short pulse duration, diverse spectral content, and high peak power, are widely used in fields including laser processing, optical storage, biomedical sciences, and laser imaging. The complex, highly-nonlinear process of ultrashort pulse evolution w...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-58630-6 |
| _version_ | 1827291621920604160 |
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| author | Xiaoxiang Han Zhiting Huang Jun Yue Jun Li Xiang’an Yan Yanwen Xia Guoqing Zhang Haiyang Zhang Caijuan Xia Yusheng Zhang |
| author_facet | Xiaoxiang Han Zhiting Huang Jun Yue Jun Li Xiang’an Yan Yanwen Xia Guoqing Zhang Haiyang Zhang Caijuan Xia Yusheng Zhang |
| author_sort | Xiaoxiang Han |
| collection | DOAJ |
| description | Abstract Ultrashort pulses, characterized by their short pulse duration, diverse spectral content, and high peak power, are widely used in fields including laser processing, optical storage, biomedical sciences, and laser imaging. The complex, highly-nonlinear process of ultrashort pulse evolution within fiber lasers is influenced by numerous aspects such as dispersion, loss, gain, and nonlinear effects. Traditionally, the split-step Fourier transforms method is employed for simulating ultrashort pulses in fiber lasers, which involves traversing multiple parameters within the fiber to attain the pulse’s optimal state. The simulation is a significantly time-consuming process. Here, we use a neural network model to fit and predict the impact of multiple parameters on the pulse characteristics within fiber lasers, enabling parameter optimization through genetic algorithms to determine the optimal pulse duration, pulse energy, and peak power. Integrating artificial intelligence algorithms simplifies the acquisition of optimal pulse parameters and enhances our understanding of multiple parameters’ impact on the pulse characteristics. The investigation of ultrashort pulse optimization based on artificial intelligence holds immense potential for laser design. |
| first_indexed | 2024-04-24T12:40:03Z |
| format | Article |
| id | doaj.art-037a99f1a7c64d5fbf8f63d330c740e5 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T12:40:03Z |
| publishDate | 2024-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-037a99f1a7c64d5fbf8f63d330c740e52024-04-07T11:14:30ZengNature PortfolioScientific Reports2045-23222024-04-0114111310.1038/s41598-024-58630-6Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithmXiaoxiang Han0Zhiting Huang1Jun Yue2Jun Li3Xiang’an Yan4Yanwen Xia5Guoqing Zhang6Haiyang Zhang7Caijuan Xia8Yusheng Zhang9School of Science, Xi’an Polytechnic UniversitySchool of Science, Xi’an Polytechnic UniversitySchool of Science, Xi’an Polytechnic UniversitySchool of Science, Xi’an Polytechnic UniversitySchool of Science, Xi’an Polytechnic UniversityResearch Center of Laser Fusion, CAEPSchool of Science, Xi’an Polytechnic UniversitySchool of Science, Xi’an Polytechnic UniversitySchool of Science, Xi’an Polytechnic UniversityHangzhou Institute of Advanced Studies, Zhejiang Normal UniversityAbstract Ultrashort pulses, characterized by their short pulse duration, diverse spectral content, and high peak power, are widely used in fields including laser processing, optical storage, biomedical sciences, and laser imaging. The complex, highly-nonlinear process of ultrashort pulse evolution within fiber lasers is influenced by numerous aspects such as dispersion, loss, gain, and nonlinear effects. Traditionally, the split-step Fourier transforms method is employed for simulating ultrashort pulses in fiber lasers, which involves traversing multiple parameters within the fiber to attain the pulse’s optimal state. The simulation is a significantly time-consuming process. Here, we use a neural network model to fit and predict the impact of multiple parameters on the pulse characteristics within fiber lasers, enabling parameter optimization through genetic algorithms to determine the optimal pulse duration, pulse energy, and peak power. Integrating artificial intelligence algorithms simplifies the acquisition of optimal pulse parameters and enhances our understanding of multiple parameters’ impact on the pulse characteristics. The investigation of ultrashort pulse optimization based on artificial intelligence holds immense potential for laser design.https://doi.org/10.1038/s41598-024-58630-6 |
| spellingShingle | Xiaoxiang Han Zhiting Huang Jun Yue Jun Li Xiang’an Yan Yanwen Xia Guoqing Zhang Haiyang Zhang Caijuan Xia Yusheng Zhang Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm Scientific Reports |
| title | Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm |
| title_full | Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm |
| title_fullStr | Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm |
| title_full_unstemmed | Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm |
| title_short | Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm |
| title_sort | optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm |
| url | https://doi.org/10.1038/s41598-024-58630-6 |
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