Multistability Manipulation by Reinforcement Learning Algorithm Inside Mode-Locked Fiber Laser Научная публикация
Журнал |
Nanophotonics
ISSN: 2192-8614 |
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Вых. Данные | Год: 2024, DOI: 10.1515/nanoph-2023-0792 | ||||||||||
Ключевые слова | multistability; harmonic mode-locked lasers; reinforcement learning; single wall carbon nanotubes; saturable absorber | ||||||||||
Авторы |
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Организации |
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Информация о финансировании (2)
1 | Российский научный фонд | 20-73-10256 (122042700104-7) |
2 | Министерство науки и высшего образования Российской Федерации | 075-03-2024-295 (124041700065-2)(FWNG-2024-0015) |
Реферат:
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.
Библиографическая ссылка:
Kokhanovskiy A.
, Kuprikov E.
, Serebrennikov K.
, Mkrtchyan A.
, Davletkhanov A.
, Bunkov A.
, Krasnikov D.
, Shashkov M.
, Nasibulin A.
, Gladush Y.
Multistability Manipulation by Reinforcement Learning Algorithm Inside Mode-Locked Fiber Laser
Nanophotonics. 2024. DOI: 10.1515/nanoph-2023-0792 WOS Scopus
Multistability Manipulation by Reinforcement Learning Algorithm Inside Mode-Locked Fiber Laser
Nanophotonics. 2024. DOI: 10.1515/nanoph-2023-0792 WOS Scopus
Даты:
Поступила в редакцию: | 9 нояб. 2023 г. |
Принята к публикации: | 3 апр. 2024 г. |
Опубликована online: | 15 апр. 2024 г. |
Идентификаторы БД:
Web of science | WOS:001202678000001 |
Scopus | 2-s2.0-85190723390 |
OpenAlex | W4394819420 |
Цитирование в БД:
Пока нет цитирований