Deep Learning for Dynamic Modeling and Coded Information Storage of Vector‐Soliton Pulsations in Mode‐Locked Fiber Lasers

Abstract Soliton pulsations are ubiquitous feature of non‐stationary soliton dynamics in mode‐locked lasers and many other physical systems. To overcome difficulties related to a huge amount of necessary computations and low efficiency of traditional numerical methods in modeling the evolution of non‐stationary solitons, a two‐parallel bidirectional long short‐term memory recurrent neural network (TP‐Bi_LSTM RNN) is proposed, with the main objective to predict dynamics of vector‐soliton pulsations (VSPs) in various complex states, whose real‐time dynamics is verified by experiments. For two examples, viz ., single‐ and bi‐periodic VSPs, with period‐21 and a combination of period‐3 and period‐43, the prediction…

• NN
  National Natural Science Foundation of China

  Awards: 12275240, 12075210, 2021FR0009, 12261131495
• SR
  Scientific Research Foundation of Zhejiang A and F University

  Award: 2021FR0009