Physics-Informed Neural Networks for Higher-Order Nonlinear Schrödinger Equations: Soliton Dynamics in External Potentials

Physics-Informed Neural Networks for Higher-Order Nonlinear Schrödinger Equations: Soliton Dynamics in External Potentials

This review summarizes the application of physics-informed neural networks (PINNs) for solving higher-order nonlinear partial differential equations belonging to the nonlinear Schrödinger equation (NLSE) hierarchy, including models with external potentials. We analyze recent studies in which PINNs h...

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Bibliographic Details
Main Authors: Leonid Serkin, Tatyana L. Belyaeva
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Mathematics
Subjects:
PINN
NLSE
solitons
external potentials
Online Access:https://www.mdpi.com/2227-7390/13/11/1882
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