Multistability manipulation by reinforcement learning algorithm inside mode-locked fiber laser

Abstract: 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.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Multistability manipulation by reinforcement learning algorithm inside mode-locked fiber laser ; volume:13 ; number:16 ; year:2024 ; pages:2891-2901 ; extent:11 ; Nanophotonics ; 13, Heft 16 (2024), 2891-2901 (gesamt 11)

Contributors, Places and Time

• Creator: Kokhanovskiy, Alexey ; Kuprikov, Evgeny ; Serebrennikov, Kirill ; Mkrtchyan, Aram ; Davletkhanov, Ayvaz ; Bunkov, Alexey ; Krasnikov, Dmitry ; Shashkov, Mikhail ; Nasibulin, Albert ; Gladush, Yuriy

Further information

• DOI: 10.1515/nanoph-2023-0792
• URN: urn:nbn:de:101:1-2407131539422.598345384731
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 14.08.2025, 10:45 AM CEST