Kokhanovskiy Alexey, Kuprikov Evgeny, Serebrennikov Kirill, Mkrtchyan Aram, Davletkhanov Ayvaz, Bunkov Alexey, Krasnikov Dmitry, Shashkov Mikhail, Nasibulin Albert, Gladush Yuriy
School of Physics and Engineering, ITMO University, St. Petersburg 197101, Russia.
Novosibirsk State University, Pirogova 2, Novosibirsk 630090, Russia.
Nanophotonics. 2024 Apr 15;13(16):2891-2901. doi: 10.1515/nanoph-2023-0792. eCollection 2024 Jul.
Fiber mode-locked lasers are nonlinear optical systems that provide ultrashort pulses at high repetition rates. However, adjusting the cavity parameters is often a challenging task due to the intrinsic multistability of a laser system. Depending on the adjustment of the cavity parameters, the optical output may vary significantly, including Q-switching, single and multipulse, and harmonic mode-locked regimes. In this study, we demonstrate an experimental implementation of the Soft Actor-Critic algorithm for generating a harmonic mode-locked regime inside a state-of-the-art fiber laser with an ion-gated nanotube saturable absorber. The algorithm employs nontrivial strategies to achieve a guaranteed harmonic mode-locked regime with the highest order by effectively managing the pumping power of a laser system and the nonlinear transmission of a nanotube absorber. Our results demonstrate a robust and feasible machine-learning-based approach toward an automatic system for adjusting nonlinear optical systems with the presence of multistability phenomena.
光纤锁模激光器是一种非线性光学系统，能够以高重复频率提供超短脉冲。然而，由于激光系统固有的多稳定性，调整腔参数往往是一项具有挑战性的任务。根据腔参数的调整，光输出可能会有显著变化，包括调Q、单脉冲和多脉冲以及谐波锁模状态。在本研究中，我们展示了软演员评论家（Soft Actor-Critic）算法在具有离子门控纳米管饱和吸收体的先进光纤激光器内生成谐波锁模状态的实验实现。该算法采用了非平凡的策略，通过有效管理激光系统的泵浦功率和纳米管吸收体的非线性传输，实现了具有最高阶数的有保证的谐波锁模状态。我们的结果展示了一种基于机器学习的稳健且可行的方法，用于构建一个自动系统，以在存在多稳定性现象的情况下调整非线性光学系统。
