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Conferences > ECEOC > 2022 > We5 > We5.32
  • European Conference on Optical Communication (ECOC) 2022
  • Technical Digest Series (Optica Publishing Group, 2022),
  • paper We5.32

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

Yuchen Song, Danshi Wang, Qirui Fan, Xiaotian Jiang, Xiao Luo, and Min Zhang

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Abstract

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.

© 2022 The Author(s)

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