1 国防科技大学前沿交叉学科学院,湖南 长沙 410073
2 国防科技大学试验训练基地,陕西 西安 710106
3 国防科技大学南湖之光实验室,湖南 长沙 410073
4 国防科技大学高能激光技术湖南省重点实验室,湖南 长沙 410073
高功率光纤激光是当前我国激光科学技术领域的前沿热点,而稀土掺杂的有源光纤是高功率光纤激光器的核心器件。与常规有源光纤不同,多折射率层有源光纤的纤芯和包层之间增加了一个或多个辅助折射率层,展现出了特殊的模场特性,有望进一步提升高功率光纤激光的输出功率。利用传统方法分析不同结构参数下多折射率层有源光纤的模场特性时,通常需要耗费较长的时间求解麦克斯韦方程组。笔者首次引入机器学习算法来预测多折射率层有源光纤的模场特性。该方法仅需要数据空间中0.1%的样本,就可以学习多折射率层有源光纤结构参数与其模场特性之间的复杂映射关系,进而实现无须求解麦克斯韦方程组的快速精准预测。该方法的平均预测误差小于0.6%,预测速度相比传统方法提升了约7000倍,为多折射率层有源光纤的模场特性分析提供了新思路。
光纤光学 人工智能 机器学习 光纤激光 有源光纤 多折射率层光纤 模场特性 中国激光
2023, 50(11): 1101013
Author Affiliations
Abstract
1 College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China
2 Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China
An all-fiberized random distributed feedback Raman fiber laser (RRFL) with mode output at 1134 nm has been demonstrated experimentally, where an intracavity acoustically induced fiber grating is employed for modal switching. The maximum output power of mode is 93.8 W with the modal purity of 82%, calculated by numerical mode decomposition technology based on stochastic parallel-gradient descent algorithm. To our best knowledge, this is the highest output power with high purity of mode generated from the RRFL. This work may pave a path towards advanced fiber lasers with special temporal and spatial characteristics for applications.
acoustically induced fiber grating LP11 mode mode decomposition random distributed feedback Raman fiber laser Chinese Optics Letters
2023, 21(2): 021406
Author Affiliations
Abstract
College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China
In recent years, machine learning, especially various deep neural networks, as an emerging technique for data analysis and processing, has brought novel insights into the development of fiber lasers, in particular complex, dynamical, or disturbance-sensitive fiber laser systems. This paper highlights recent attractive research that adopted machine learning in the fiber laser field, including design and manipulation for on-demand laser output, prediction and control of nonlinear effects, reconstruction and evaluation of laser properties, as well as robust control for lasers and laser systems. We also comment on the challenges and potential future development.
Author Affiliations
Abstract
College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha, China
In this work, a confined-doped fiber with the core/inner-cladding diameter of 40/250 μm and a relative doping ratio of 0.75 is fabricated through a modified chemical vapor deposition method combined with the chelate gas deposition technique, and subsequently applied in a tandem-pumped fiber amplifier for high-power operation and transverse mode instability (TMI) mitigation. Notably, the impacts of the seed laser power and mode purity are preliminarily investigated through comparative experiments. It is found that the TMI threshold could be significantly affected by the seed laser mode purity. The possible mechanism behind this phenomenon is proposed and revealed through comprehensive comparative experiments and theoretical analysis. Finally, a maximum output power of 7.49 kW is obtained with the beam quality factor of approximately 1.83, which is the highest output power ever reported in a forward tandem-pumped confined-doped fiber amplifier. This work could provide a good reference and practical solution to improve the TMI threshold and realize high-power high-brightness fiber lasers.
confined-doped fiber fiber laser good beam quality high power transverse mode instability mitigation High Power Laser Science and Engineering
2022, 10(6): 06000e44
Author Affiliations
Abstract
College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China
We found the beam quality factor M2 of the fundamental mode as a function of wavelength is U-shaped in the working photonic bandgap (PBG) of an all-solid PBG fiber (AS-PBGF) for the first time, to the best of our knowledge, and our simulation results also match well with the phenomenon. The normal band that is near the high-frequency edge of the third PBG integrates the lowest M2 and single-mode operation simultaneously, while the other two edge regions suffer from anomalous variation of M2 versus wavelength. The general applicability of this finding can be further extended to other PBGs and also other representative structures in the AS-PBGF field.
all-solid photonic bandgap fiber beam quality factor U-shaped curve photonic bandgap Chinese Optics Letters
2022, 20(1): 010602
1 国防科技大学前沿交叉学科学院, 湖南 长沙 410073
2 高能激光技术湖南省重点实验室, 湖南 长沙 410073
基于自主研制的双锥形掺镱双包层光纤,开展了全光纤高功率光纤激光放大实验。激光系统实现了中心波长为1080nm、最高功率为4 kW的单模激光输出,其光光效率和斜率效率分别为82%和83%,质量因子(M2)为1.33,拉曼抑制比为44dB。实验结果表明,双锥形光纤具有同时提高非线性效应和模式不稳定性效应阈值的优势,有利于进一步提升高光束质量光纤激光器的输出功率。
激光器 高功率光纤激光器 锥形光纤 单模 受激拉曼散射 模式不稳定
Author Affiliations
Abstract
1 College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China
2 Hypervelocity Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China
3 e-mail: shandapengfei@126.com
4 e-mail: zhoupu203@163.com
High-power mode-programmable orbital angular momentum (OAM) beams have received substantial attention in recent years. They are widely used in optical communication, nonlinear frequency conversion, and laser processing. To overcome the power limitation of a single beam, coherent beam combining (CBC) of laser arrays is used. However, in specific CBC systems used to generate structured light with a complex wavefront, eliminating phase noise and realizing flexible phase modulation proved to be difficult challenges. In this paper, we propose and demonstrate a two-stage phase control method that can generate OAM beams with different topological charges from a CBC system. During the phase control process, the phase errors are preliminarily compensated by a deep-learning (DL) network, and further eliminated by an optimization algorithm. Moreover, by modulating the expected relative phase vector and cost function, all-electronic flexible programmable switching of the OAM mode is realized. Results indicate that the proposed method combines the characteristics of DL for undesired convergent phase avoidance and the advantages of the optimization algorithm for accuracy improvement, thereby ensuring the high mode purity of the generated OAM beams. This work could provide a valuable reference for future implementation of high-power, fast switchable structured light generation and manipulation.
Photonics Research
2020, 8(5): 05000715