TY - JOUR

T1 - Multistability manipulation by reinforcement learning algorithm inside mode-locked fiber laser

AU - Kokhanovskiy, Alexey

AU - Kuprikov, Evgeny

AU - Serebrennikov, Kirill

AU - Mkrtchyan, Aram

AU - Davletkhanov, Ayvaz

AU - Bunkov, Alexey

AU - Krasnikov, Dmitry

AU - Shashkov, Mikhail

AU - Nasibulin, Albert

AU - Gladush, Yuriy

N1 - Research funding: The work of A.K. and Y.G. (initiation of the study, conceptualization, development of the algorithms, writing the article) was financially supported by ITMO-MIPT-Skoltech Clover Program. D.K. and A.B. thank RSF grant 20-73-10256 (synthesis of carbon nanotubes with tailored optical spectrum). The work of K.S. (arrangement and automatization of the experimental setup) was supported by the state budget of IAE SB RAS (project No. FWNG-2024-0015).

PY - 2024/7/1

Y1 - 2024/7/1

N2 - 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.

AB - 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.

KW - harmonic mode-locked lasers

KW - multistability

KW - reinforcement learning

KW - saturable absorber

KW - single wall carbon nanotubes

UR - https://www.mendeley.com/catalogue/1c207148-8cb8-3655-8588-56e702479d17/

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85190723390&origin=inward&txGid=0997058bfa8c61888c07acb9ef3e77c6

U2 - 10.1515/nanoph-2023-0792

DO - 10.1515/nanoph-2023-0792

M3 - Article

VL - 13

SP - 2891

EP - 2901

JO - Nanophotonics

JF - Nanophotonics

SN - 2192-8606

IS - 16

ER -