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Physics-Informed Neural Operator for Fast and Scalable Optical Fiber Channel Modelling in Multi-Span Transmission

We propose efficient modelling of optical fiber channel via NLSE-constrained physics-informed neural operator without reference solutions. This method can be easily scalable for distance, sequence length, launch power, and signal formats, and is implemented for ultra-fast simulations of 16-QAM signal transmission with ASE noise.

preprint2022arXivOpen access
Yuchen SongDanshi WangQirui FanXiaotian JiangXiao LuoMin Zhang
eess.SPphysics.optics
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Open access6 authors2 topics
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Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Yuchen SongDanshi WangQirui FanXiaotian JiangXiao LuoMin Zhang

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