Recent advances in machine learning-driven fiber lasers

Geng Xiang; Zhao Chunxiao; Cao Jianing; Li Jingyu; Wu Hanshuo; Wang Peng; Ye Yun; Xi Xiaoming; Zhang Hanwei; Wang Xiaolin

doi:10.11884/HPLPB202638.250284

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Article Navigation > High Power Laser and Particle Beams > 2026 > Accepted Manuscript

Geng Xiang, Zhao Chunxiao, Cao Jianing, et al. Recent advances in machine learning-driven fiber lasers[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202638.250284

Citation:

Geng Xiang, Zhao Chunxiao, Cao Jianing, et al. Recent advances in machine learning-driven fiber lasers[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202638.250284

Geng Xiang, Zhao Chunxiao, Cao Jianing, et al. Recent advances in machine learning-driven fiber lasers[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202638.250284

Citation:

Geng Xiang, Zhao Chunxiao, Cao Jianing, et al. Recent advances in machine learning-driven fiber lasers[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202638.250284

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Recent advances in machine learning-driven fiber lasers

doi: 10.11884/HPLPB202638.250284

Geng Xiang^{1, 2
,},
Zhao Chunxiao^{1, 2},
Cao Jianing¹,
Li Jingyu¹,
Wu Hanshuo^{1, 2},
Wang Peng^{1, 2},
Ye Yun^{1, 2},
Xi Xiaoming^{1, 2},
Zhang Hanwei^{1, 2},
Wang Xiaolin^{1, 2
,
,}

1.
College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China
2.
Nanhu Laser Laboratory, National University of Defense Technology, Changsha 410073, China

Received Date: 2025-09-05
Accepted Date: 2025-12-25
Rev Recd Date: 2025-12-30

Available Online: 2026-01-17

Abstract

Abstract

Fiber laser technology, after years of development, has established an indispensable role in modern industrial and scientific research. However, traditional performance optimization methods have significant limitations in terms of efficiency, speed, and accuracy, making it difficult to meet the demands of high-performance and high-efficiency application scenarios. The deep integration of machine learning and fiber laser has provided a new technical paradigm for multidimensional performance optimization of fiber laser systems, significantly enhancing laser performance while expanding technological boundaries. This paper briefly introduces the classification of machine learning, applicable domains and corresponding application scenarios, with a focus on reviewing recent advances in laser device design, laser simulation and prediction, intelligent control of lasers and output characteristics, as well as the measurement and characterization of laser parameters. Based on the current technical challenges in data dependency, generalization ability, interpretability, and computational efficiency, future development trends of machine learning in fiber lasers are projected.
- machine learning,
- fiber lasers,
- neural network,
- intelligent control,
- performance optimization

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References(117)

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