中心凹陷型少模掺铒光纤中的模场调控与增益均衡

Wenxuan, 徐文轩 Xu; Li, 裴丽 Pei; Jianshuai, 王建帅 Wang; Zhiqi, 李祉祺 Li; Qi, 赵琦 Zhao; Jingjing, 郑晶晶 Zheng; Jing, 李晶 Li; Tigang, 宁提纲 Ning; Li, 钟力 Zhong

doi:10.3788/aos202242.2106002

光学学报

2022

DOI: 10.3788/aos202242.2106002

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中心凹陷型少模掺铒光纤中的模场调控与增益均衡

徐文轩 Xu Wenxuan¹,

裴丽 Pei Li²,

王建帅 Wang Jianshuai³

et al.

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2024

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M-type refractive index profile erbium-doped fiber for high-efficiency multicore EDFA

Gu,

He,

Yin

et al. 2024

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Cladding-pumped multicore erbium-doped fiber is an important element for future spatial division multiplexing (SDM) amplification. We propose an M-type erbium-doped multicore fiber to achieve high-efficiency SDM amplification. The performance of cladding-pumped erbium-doped fiber with a central refractive index depression has been investigated, and the M-type fiber has better amplification performance than conventional fibers by reducing the signal mode overlap with the doped region. The experiment results show that the M-type 4-core erbium-doped fiber has a gain improvement of 2.8 dB compared with conventional 4-core fiber. The pump conversion efficiency (PCE) has been enhanced from 4.47% to 8.01%. For a 7.0 W pump power at 976 nm, the M-type fiber exhibits an average gain of 20.0 dB and an average noise fiber of 6.8 dB at the L-band. The core-to-core gain variation is less than 1.6 dB.

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M-type refractive index profile erbium-doped fiber for high-efficiency multicore EDFA

Gu,

He,

Yin

et al. 2024

Opt. Express

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Confinement loss prediction in diverse anti-resonant fibers through neural networks

Zhenyu,

Tigang,

et al. 2024

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In this work, genetic algorithm (GA) is employed to optimize convolutional neural networks (CNNs) for predicting the confinement loss (CL) in anti-resonant fibers (ARFs), achieving a prediction accuracy of CL magnitude reached 90.6%, which, to the best of our knowledge, represents the highest accuracy to date and marks the first instance of using a single model to predict CL across diverse ARF structures. Different from the previous definition of ARF structures with parameter groups, we use anchor points to describe these structures, thus eliminating the differences in expression among them. This improvement allows the model to gain insight into the specific structural characteristics, thereby enhancing its generalization capabilities. Furthermore, we demonstrate a particle swarm optimization algorithm (PSO), driven by our model, for the design of ARFs, validating the model’s robust predictive accuracy and versatility. Compared with the calculation of CL by finite element method (FEM), this model significantly reduces the cost time, and provides a speed-up method in fiber design driven by numerical calculation.

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中心凹陷型少模掺铒光纤中的模场调控与增益均衡

Cited by 2 publications

References 0 publications

M-type refractive index profile erbium-doped fiber for high-efficiency multicore EDFA

M-type refractive index profile erbium-doped fiber for high-efficiency multicore EDFA

Confinement loss prediction in diverse anti-resonant fibers through neural networks

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