This learning guide breaks down Optiland into a series of tutorials that cover the basic concepts and functionalities of the package. Each tutorial is a self-contained Jupyter notebook that demonstrates how to perform a specific task using Optiland. The tutorials are designed to be followed sequentially, starting with an introduction to Optiland and progressing to more advanced topics.
1. Introduction to Optiland
2. Real Raytracing & Analysis
3. Aberrations
4. OPD, PSF, & MTF
5. Optimization
6. Coatings & Polarization
- Tutorial 6a - Introduction to Coatings
- Tutorial 6b - Introduction to Polarization
- Tutorial 6c - Multilayer Stack
- Tutorial 6d - Dichroic Mirror Optimization for Polarization Separation
- Tutorial 6e - Color Evolution of a Thin-Film
- Tutorial 6f : Anti-Reflective Coating
- Tutorial 6h: Needle Synthesis for Thin Film Design
- Part 1: Broadband AR Coating (R < 1%)
- Part 2: Dichroic Beamsplitter at 550 nm
- Tutorial 6i: Thin Film Tolerance Analysis
7. Advanced Optical Design
8. Tolerancing
9. Lens Catalogue Integration
10. Extending Optiland
11. Extended Source Modeling
12. Machine Learning in Optical Design
These examples demonstrate how Optiland can be used in conjunction with machine learning to solve optical design problems. Concepts in machine and deep learning are also covered. Note that these are hosted on the LensAI repository.
- Tutorial 11a - Random Forest Regressor to Predict Optimal Lens Properties
- Tutorial 11b - Ray Path Failure Classification Model
- Tutorial 11c - Surrogate Ray Tracing Model: Using Optiland and PyTorch
- Tutorial 11d - Super-Resolution GAN to Enhance Wavefront Map Data
- Tutorial 11e - Optimization of Aspheric Lenses via Reinforcement Learning
- Tutorial 11f - Predicting Lens Misalignments Using Regression Models