自动锁模光纤激光器研究进展

 

 

摘要：为解决基于非线性偏振旋转（NPR）的被动锁模光纤激光器（MLFL）抗环境干扰能力差和偏振难调等问题，基于不同算法和硬件的自动MLFL相继被提出并取得重大突破。其中，简单的遍历算法在自动锁模方案验证方面应用广泛，机器学习算法在仿真层面可以实现高效的自动锁模，最优化算法因其能进行高效的目标搜索而成为自动锁模的研究最热点。
关键词：自动锁模；MLFL；NPR


Abstract: To solve the problems of poor environmental disturbances resistance and difficult polarization adjustment of passive mode-locked fiber lasers based on nonlinear polarization rotation (NPR), automatic mode-locking fiber lasers (MLFL) based on different algorithms and hardware have been proposed successively and made great breakthroughs. Among them, the simple traversal algorithm is widely used in the verification of automatic mode-locked schemes. Machine learning algorithms can achieve efficient automatic mode-locking in the simulation. The optimization algorithm has become the hotspot of research on automatic mode-locking due to its efficient target search.
Keywords: automatic mode-locking; MLFL; NPR