Neural Operators for Helmholtz Equation

Welcome to the documentation for the Neural Operators for Helmholtz Equation project! This project focuses on the application of advanced neural operator techniques to solve the Helmholtz equation in various parameterized geometries. The approach integrates deep learning with physical modeling of domains.

Contents

• Code Coverage
• nos
  • nos package
• Examples

Introduction

The Helmholtz equation is a fundamental partial differential equation in physics, particularly in the fields of acoustics, electromagnetics, and quantum mechanics. In this project, we develop and utilize neural operators, a form of deep learning model, to solve the Helmholtz equation across different parameterized geometries. This approach aims to overcome the limitations of traditional numerical methods, offering speed and flexibility for complex geometries.

API Reference

The nos section offers detailed descriptions of the functions, classes, and methods available in this project.

Examples

Explore practical applications and see the neural operators in action in the Examples section.