A Physics-Informed Neural Network for Higher-Order Soliton Compression in Fibers

被引：0
|
作者：
Wu, Jinhong [1 ]
Wang, Zimiao [1 ]
Li, Qian [1 ]
机构：
[1] Peking Univ, Sch Elect & Comp Engn, Shenzhen 518055, Peoples R China
来源：
2022 ASIA COMMUNICATIONS AND PHOTONICS CONFERENCE, ACP | 2022年
关键词：
PINN; higher-order soliton compression;
D O I：
10.1109/ACP55869.2022.10088889
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We construct a physics-informed neural network to predict the higher-order soliton compression. Through embedding a partial differential equation into the neural network, the evolution of soliton in nonlinear fiber can be predicted accurately and efficiently.
引用
收藏
页码：71 / 73
页数：3
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