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Updated: Jul 23, 2025

Rapid Repetition Rate Fluctuation Measurement of Soliton Crystals in a Microresonator
Published on: December 15, 2021
PT-symmetric solitons and parameter discovery in self-defocusing saturable nonlinear Schrödinger equation via
Bo-Wei Zhu1, Wen-Bo Bo1, Qi-Hao Cao1
1College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Lin'an 311300, China.
Abstract:
We propose a physical information neural network with learning rate decay strategy (LrD-PINN) to predict the dynamics of symmetric, asymmetric, and antisymmetric solitons of the self-defocusing saturable nonlinear Schrödinger equation with the PT-symmetric potential and boost the predicted evolutionary distance by an order of magnitude. Taking symmetric solitons as an example, we explore the advantages of the learning rate decay strategy, analyze the anti-interference performance of the model, and optimize the network structure. In addition, the coefficients of the saturable nonlinearity strength and the modulation strength in the PT-symmetric potential are reconstructed from the dataset of symmetric soliton solutions. The application of more advanced machine learning techniques in the field of nonlinear optics can provide more powerful tools and richer ideas for the study of optical soliton dynamics.
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