Multistability Manipulation by Reinforcement Learning Algorithm Inside Mode-Locked Fiber Laser | Sciact - CRIS-system of Boreskov Institute of Catalysis

Multistability Manipulation by Reinforcement Learning Algorithm Inside Mode-Locked Fiber Laser Full article

Journal

Nanophotonics
ISSN: 2192-8614

Output data

Year: 2024, Volume: 13, Number: 16, Pages: 2891–2901 Pages count : 11 DOI: 10.1515/nanoph-2023-0792

Tags

multistability; harmonic mode-locked lasers; reinforcement learning; single wall carbon nanotubes; saturable absorber

Authors

Kokhanovskiy Alexey ¹ , Kuprikov Evgeny ² , Serebrennikov Kirill ^2,3 , Mkrtchyan Aram ⁴ , Davletkhanov Ayvaz ⁴ , Bunkov Alexey ⁴ , Krasnikov Dmitry ⁴ , Shashkov Mikhail ⁵ , Nasibulin Albert ⁴ , Gladush Yuriy ⁴

Affiliations

1	School of Physics and Engineering, ITMO University, St. Petersburg 197101, Russia
2	Novosibirsk State University, Pirogova 2, Novosibirsk 630090, Russia
3	Institute of Automation and Electrometry SB RAS, 1 Ac. Koptyug ave., Novosibirsk 630090, Russia
4	Skolkovo Institute of Science and Technology, Moscow 121205, Russia
5	Boreskov Institute of Catalysis SB RAS, Novosibirsk 630090, Russia

Funding (2)

1	Russian Science Foundation	20-73-10256 (122042700104-7)
2	Ministry of Science and Higher Education of the Russian Federation	075-03-2024-295 (124041700065-2)(FWNG-2024-0015)

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.

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. V.13. N16. P.2891–2901. DOI: 10.1515/nanoph-2023-0792 WOS Scopus РИНЦ PMID OpenAlex

Submitted:	Nov 9, 2023
Accepted:	Apr 3, 2024
Published online:	Apr 15, 2024
Published print:	Jul 1, 2024

Web of science:	WOS:001202678000001
Scopus:	2-s2.0-85190723390
Elibrary:	67230888
PMID:	39634311
OpenAlex:	W4394819420

DB	Citing
OpenAlex	1
Web of science	2
Scopus	2