Adaptive genetic algorithm-based 2 μm intelligent mode-locked fiber laser

Xian, Anhua; Cao, Xue; Liu, Yangyu; Wang, Yibo; Yin, Xuejian; Liu, Guangmiao; Zhou, Wei; Wang, Haotian; Huang, H. K.; Tang, Dingyuan; Shen, Deyuan

doi:10.1364/osac.440960

Cited by 5 publications

(2 citation statements)

References 34 publications

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“…8c). Furthermore, the AI-enabled automatic control is feasible for mode-locked lasers in the 2-μm band [101] and single-cavity dual-comb lasers [102], showing the strong adaptability of AI to different types of lasers.…”

Section: Automatic Controlmentioning

confidence: 99%

Artificial Intelligence-Enabled Mode-Locked Fiber Laser: A Review

Ma,

2023

Nanomanuf Metrol

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Owing to their compactness, robustness, low cost, high stability, and diffraction-limited beam quality, mode-locked fiber lasers play an indispensable role in micro/nanomanufacturing, precision metrology, laser spectroscopy, LiDAR, biomedical imaging, optical communication, and soliton physics. Mode-locked fiber lasers are a highly complex nonlinear optical system, and understanding the underlying physical mechanisms or the flexible manipulation of ultrafast laser output is challenging. The traditional research paradigm often relies on known physical models, sophisticated numerical calculations, and exploratory experimental attempts. However, when dealing with several complex issues, these traditional approaches often face limitations and struggles in finding effective solutions. As an emerging data-driven analysis and processing technology, artificial intelligence (AI) has brought new insights into the development of mode-locked fiber lasers. This review highlights the areas where AI exhibits potential in accelerating the development of mode-locked fiber lasers, including nonlinear dynamics prediction, ultrashort pulse characterization, inverse design, and automatic control of mode-locked fiber lasers. Furthermore, the challenges and potential future development are discussed.

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Section: Automatic Controlmentioning

confidence: 99%

Artificial Intelligence-Enabled Mode-Locked Fiber Laser: A Review

Ma,

2023

Nanomanuf Metrol

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“…21 In previous work, we successfully achieved stable noiselike mode-locked pulse output using an adaptive GA in TDFL. 22 In this work, we further explored the dynamic evolutions of polarization control parameters under algorithm optimization in one-dimensional, two-dimensional, and three-dimensional parameter space in TDFL.…”

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confidence: 99%

Polarization control parameters evolution of genetic algorithm‐based 2 µm Tm‐doped fiber laser

Liu,

Wang,

Xian

et al. 2024

Micro & Optical Tech Letters

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In this paper, we explored the different performances of the evolution of polarization control parameters under algorithm optimization in one‐dimensional, two‐dimensional, and three‐dimensional parameter space. We found that the genetic algorithm (GA) operation has a typical converging trend as the epoch increasing of groups in ultra‐fast pulse generation. The corresponding deviations were calculated to be 10.8%, 11.2%, and 5.0%, respectively, which is different from the traversal algorithm operation. The typical noise‐like pulse state was effectively automatically searched at different length cavities, with center wavelengths of 1973, 1988.7, and 2002.7 nm, repetition rate of 9.4, 10.4, and 5.4 MHz, and typical spike duration of ~224 fs. Our research shows the effectiveness of the GA in searching and controlling the ultrashort pulse output of a 2‐µm thulium‐doped fiber laser.

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Intelligent Laser Emitting and Mode Locking of Solid‐State Lasers Using Human‐Like Algorithms

Guo,

Fan,

et al. 2024

Laser & Photonics Reviews

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Solid‐state lasers based on mode‐locked technology are widely studied for their strong ability of average or peak power scaling and wide wavelength coverage. However, it usually takes a long time and a lot of effort to manually align an ultrafast solid‐state laser to achieve laser emission and stable mode‐locking. Here, an approach based on intelligent human‐like algorithms is proposed for aligning a solid‐state ultrafast laser system. The intelligent system is based on multi‐algorithm fusion and can fully simulate the process of observation, analysis, decision, and action of an experienced experimenter in the adjustment of the laser alignment and mode‐locking. The intelligent adjustment starts from the state of no laser emission, adopts the neural network, the modified augmented random search (ARS) algorithm, random search, and sliding window strategy, and takes the fluorescence and speckle patterns as indications to realize the laser emission and stable mode‐locking automatically. Several validation experiments are conducted using this intelligent system, and the stable mode‐locked pulses can be achieved within 40 s. This technology provides an efficient solution to the ultrafast solid‐state laser that requires full automatic laser emitting and stable mode‐locking for the first time.

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Adaptive genetic algorithm-based 2 μm intelligent mode-locked fiber laser

Cited by 5 publications

References 34 publications

Artificial Intelligence-Enabled Mode-Locked Fiber Laser: A Review

Artificial Intelligence-Enabled Mode-Locked Fiber Laser: A Review

Polarization control parameters evolution of genetic algorithm‐based 2 µm Tm‐doped fiber laser

Intelligent Laser Emitting and Mode Locking of Solid‐State Lasers Using Human‐Like Algorithms

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