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

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.