TorchRDIT Documentation

Welcome to the TorchRDIT documentation. TorchRDIT is an advanced software package designed for the inverse design of meta-optics devices, utilizing an eigendecomposition-free implementation of Rigorous Diffraction Interface Theory (R-DIT). It provides a GPU-accelerated and fully differentiable framework powered by PyTorch, enabling the efficient optimization of photonic structures.

Key Features

• Differentiable: Built on PyTorch for seamless integration with deep learning and optimization
• High-Performance: Efficient implementations of RCWA and RDIT algorithms
• Flexible: Support for complex geometries, dispersive materials, and various layer structures
• Extensible: Easy to integrate into machine learning and inverse design workflows

Documentation

User Guide

• Getting Started - Installation and basic usage
• Examples - Detailed examples showing how to use TorchRDIT

API Reference

• API Overview
• Algorithm Module - Implementation of electromagnetic solvers
• Builder Module - Fluent API for creating simulations
• Cell Module - Cell geometry definitions
• Constants Module - Physical constants and enumerations
• Layers Module - Layer definitions and operations
• Materials Module - Material property definitions
• Material Proxy Module - Material data handling and unit conversion
• Observers Module - Progress tracking and reporting
• Results Module - Structured data containers for simulation results
• Shapes Module - Shape generation for photonic structures
• Solver Module - Core solver functionality
• Utils - Utility functions
• Visualization - Tools for visualizing results

Examples

TorchRDIT comes with several example files in the examples/ directory

For more detailed explanations of each example, see the Examples page.