Paper ID: 2411.04511

Improve the Fitting Accuracy of Deep Learning for the Nonlinear Schrödinger Equation Using Linear Feature Decoupling Method

Yunfan Zhang, Zekun Niu, Minghui Shi, Weisheng Hu, Lilin Yi

We utilize the Feature Decoupling Distributed (FDD) method to enhance the capability of deep learning to fit the Nonlinear Schrodinger Equation (NLSE), significantly reducing the NLSE loss compared to non decoupling model.

Submitted: Nov 7, 2024