base on Comprehensive optical design, optimization, and analysis in Python, including GPU-accelerated and differentiable ray tracing via PyTorch.  [](https://optiland.readthedocs.io/en/latest/?badge=latest) [](https://codecov.io/github/HarrisonKramer/optiland) [](https://codeclimate.com/github/HarrisonKramer/optiland/maintainability)  [](https://opensource.org/licenses/MIT) [](https://doi.org/10.5281/zenodo.14588961) [](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%7C%203.12%20%7C%203.13%20-blue) <div align="center"> <a href="https://optiland.readthedocs.io/"> <img src="https://github.com/HarrisonKramer/optiland/raw/master/docs/images/optiland.svg" alt="Optiland"> </a> </div> <!-- TABLE OF CONTENTS --> <details> <summary>Table of Contents</summary> <ol> <li><a href="#introduction">Introduction</a></li> <li><a href="#documentation">Documentation</a></li> <li><a href="#installation">Installation</a></li> <li><a href="#key-features">Functionalities</a></li> <li><a href="#learning-guide">Learning Guide</a></li> <li><a href="#roadmap">Roadmap</a></li> <li><a href="#license">License</a></li> <li><a href="#contact-and-support">Contact and Support</a></li> </ol> </details> --- ## Introduction **Optiland** provides a flexible Python interface for optical system design—whether you're tracing rays through traditional lenses or training differentiable models with PyTorch. It supports both classical engineering workflows and cutting-edge research needs. It lets you: - ⚙️ Build lens and mirror systems with a clean, object-oriented API - 🔍 Trace rays through multi-surface optical assemblies, including aspherics and freeforms - 📊 Analyze paraxial properties, wavefront errors, PSFs/MTFs, and scatter behavior - 🧠 Optimize via traditional merit functions *or* autograd-enabled differentiable backends - 🎨 Visualize interactively in 2D (Matplotlib) and 3D (VTK) Under the hood, Optiland uses **NumPy** for fast CPU calculations and **PyTorch** for GPU acceleration and automatic differentiation. Switch between engines depending on your use case—with the same interface. <figure style="text-align: center;"> <img src="https://github.com/HarrisonKramer/optiland/raw/master/docs/images/telephoto.png" alt="U.S. patent 2959100" style="width: 800px;"> </figure> Python code to generate this 3D visualization: ```python from optiland.samples.objectives import ReverseTelephoto lens = ReverseTelephoto() lens.draw3D() ``` 🚀 **Quickstart** 1. 🌟 [Quickstart Tutorial](https://optiland.readthedocs.io/en/latest/examples/Tutorial_1a_Optiland_for_Beginners.html) – build your first lens in 5 minutes 2. 📚 [Full Learning Guide](https://optiland.readthedocs.io/en/latest/learning_guide.html) – in-depth guide to mastering Optiland 3. 🖼️ [Example Gallery](https://optiland.readthedocs.io/en/latest/gallery/introduction.html) – visual showcase of designs and core features 4. 📝 [Cheat Sheet](https://optiland.readthedocs.io/en/latest/cheat_sheet.html) - an up-to-date cheat sheet to get you started ASAP with your first optical system --- ## Documentation Optiland's full documentation is available on [Read the Docs](https://optiland.readthedocs.io/). Whether you're just getting started or exploring advanced features, here are the best entry points: - **🔍 Quick Start**: The [Cheat Sheet](https://optiland.readthedocs.io/en/latest/cheat_sheet.html) offers a concise overview of core concepts and commands. - **🧪 Example Gallery**: Browse the [Gallery](https://optiland.readthedocs.io/en/latest/gallery/introduction.html) for real-world lens designs, visualizations, and analysis workflows using Optiland. - **🛠️ Developer Resources**: - The [Developer's Guide](https://optiland.readthedocs.io/en/latest/developers_guide/introduction.html) explains the internal architecture and design of Optiland. - The [API Reference](https://optiland.readthedocs.io/en/latest/api/api_introduction.html) provides detailed documentation for all public classes, functions, and modules. ## Installation - **Core only** ```bash pip install optiland ``` - **With CPU‑only PyTorch** ```bash pip install optiland[torch] ``` - **GPU‑enabled PyTorch** - After installing Optiland, install a CUDA build of PyTorch manually: ```bash pip install optiland pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 ``` For more details, see the [installation guide](https://optiland.readthedocs.io/en/latest/installation.html) in the docs. ## Key Features - **Differentiable & Configurable Backends** Swap seamlessly between NumPy (CPU) and PyTorch (GPU + autograd). Enables integration of optical simulations into ML/DL pipelines. - **Flexible Lens Construction** Easily define optical systems, with support for spherical, aspheric, and freeform geometries. - **2D and 3D Visualization** Visualize optical layouts with matplotlib and VTK. - **Ray Tracing (Paraxial and Real)** Supports paraxial approximations and full real-ray tracing, with accurate handling of aspheric and freeform surfaces. - **Polarization Ray Tracing** Track polarization effects using vectorial ray tracing, including birefringence and coating interactions. - **Aberration and Paraxial Analysis** Tools for classical paraxial analysis and low-order aberration extraction, including chief and marginal ray tracing. - **Full Real Analysis Suite** Compute spot diagrams, OPD and ray aberration fans, PSF, MTF, and Zernike coefficients across fields and wavelengths. - **Material and Glass Catalogues** Built-in access to refractiveindex.info data, plus support for custom material models. - **Design Optimization** Local gradient-based and global stochastic optimization, with customizable merit functions and constraint handling. - **Tolerancing Framework** Monte Carlo and sensitivity analyses for evaluating robustness under manufacturing and alignment variations. - **Coating and Scattering Support** Evaluate BSDF-based surface scatter and multilayer coatings using both built-in and user-defined models. - **Zemax File Import** Convert legacy designs from Zemax files into Optiland’s internal representation for further simulation or analysis. The code itself is in constant flux and new functionalities are always being added. ## Learning Guide This guide gives a step-by-step approach to learning how to use Optiland. 1. **Introduction to Optiland** - [Tutorial 1a - Optiland for Beginners](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_1a_Optiland_for_Beginners.ipynb) - Lens entry - Material selection - Aperture, field and wavelength selection - Drawing a lens in 2D and 3D - [Tutorial 1b - Determining Lens Properties](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_1b_Lens_Properties.ipynb) - Focal length - Magnification - F-Number, Entrance/Exit pupil sizes & positions - Focal, Principal, and Nodal points, etc. - [Tutorial 1c - Saving and Loading Lenses](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_1c_Save_and_Load_Files.ipynb) - Saving and loading lens files in a json format - [Tutorial 1d - Using the Material Database](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_1d_Material_Database.ipynb) - Defining materials for glass, chemicals, organics, gases, or using ideal or parameterized materials. - [Tutorial 1e - Non-rotationally Symmetric Systems](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_1e_Non_Rotationally_Symmetric_Systems.ipynb) - Coordinate systems in Optiland and how to design non-rotationally symmetric systems - [Tutorial 1f - Differentiable Raytracing Hello World](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_1f_Differentiable_Ray_Tracing_Hello_World.ipynb) - Your first steps with DRT using the PyTorch backend. 2. **Real Raytracing & Analysis** - [Tutorial 2a - Tracing & Analyzing Rays](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_2a_Tracing_&_Analyzing_Rays.ipynb) - How to trace rays through a system - Analyzing ray paths & properties - [Tutorial 2b - Tilting & De-centering Components](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_2b_Tilting_&_Decentering_Components.ipynb) - Tracing rays through misaligned components - [Tutorial 2c - Monte Carlo Raytracing Methods](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_2c_Monte_Carlo_Raytracing.ipynb) - How variations in lens properties impact lens performance - [Tutorial 2d - Aspheric Components](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_2d_Raytracing_Aspheres.ipynb) - Modeling even aspheres 3. **Aberrations** - [Tutorial 3a - Common aberration analyses/plots](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_3a_Common_Aberration_Analyses.ipynb) - Spot diagrams - Ray fans - Y-Ybar plots - Distortion / Grid distortion plots - Field curvature plots - RMS spot size & wavefront error vs. field - Pupil aberration - [Tutorial 3b - 1st & 3rd-Order Aberrations](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_3b_First_&_Third_Order_Aberrations.ipynb) - Calculation of seidel, 1st & 3rd-order aberrations - [Tutorial 3c - Chromatic Aberrations](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_3c_Chromatic_Aberrations.ipynb) - Achromatic doublet to reduce chromatic aberrations 4. **Optical Path Difference (OPD), Point Spread Functions (PSF) & Modulation Transfer Function (MTF)** - [Tutorial 4a - Optical Path Difference](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_4a_Optical_Path_Difference_Calculation.ipynb) - OPD fans and plots - [Tutorial 4b - PSF & MTF Calculation](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_4b_PSF_&_MTF_Calculation.ipynb) - Geometric MTF - FFT-based PSF/MTF - Huygens PSF - [Tutorial 4c - Zernike Decomposition](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_4c_Zernike_Decomposition.ipynb) - Decomposing wavefront using Zernike polynomials - Coefficient types: Zernike standard, Zernike fringe, Zernike Noll 5. **Optimization** - [Tutorial 5a - Simple Optimization](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_5a_Simple_Optimization.ipynb) - Operand and variable definition - Local optimization - [Tutorial 5b - Advanced Optimization](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_5b_Advanced_Optimization.ipynb) - Global optimization - [Tutorial 5c - Optimization Case Study](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_5c_Optimization_Case_Study.ipynb) - Complete process of designing a Cooke triplet - [Tutorial 5d - User-defined Optimization Metrics](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_5d_User_Defined_Optimization.ipynb) - Customized optimization 6. **Coatings & Polarization** - [Tutorial 6a - Introduction to Coatings](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_6a_Introduction_to_Coatings.ipynb) - Simple coatings in Optiland - Impact of coatings on system performance - [Tutorial 6b - Introduction to Polarization](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_6b_Introduction_to_Polarization.ipynb) - Basics of polarization in Optiland - Analyzing polarization performance 7. **Advanced Optical Design** - [Tutorial 7a - Lithographic Projection System](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_7a_Lithographic_Projection_System.ipynb) - Optimizing and Analyzing a Complex Lithography System - [Tutorial 7b - Surface Roughness & Scattering](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_7b_Surface_Roughness_&_Scattering.ipynb) - Lambertian and Gaussian scatter models - [Tutorial 7c - Freeform Surfaces](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_7c_Freeform_Surfaces.ipynb) - Designing non-standard optical systems with freeform surfaces - [Tutorial 7d - Three Mirror Anastigmat](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_7d_Three_Mirror_Anastigmat.ipynb) - Off-axis reflective telescope with freeform surfaces 8. **Tolerancing** - [Tutorial 8a - Introduction to Tolerancing](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_8a_Tolerancing_Sensitivity_Analysis.ipynb) - Sensitivity studies - [Tutorial 8b - Advanced Tolerancing](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_8b_Monte_Carlo_Analysis.ipynb) - Monte Carlo-based Tolerancing 9. **Lens Catalogue Integration** - [Tutorial 9a - Edmund Optics Catalogue](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_9a_Edmund_Optics_Catalogue.ipynb) - Reading Zemax files - Reading and analyzing an aspheric lens - [Tutorial 9b - Thorlabs Catalogue](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_9b_Thorlabs_Catalogue.ipynb) - Reading and analyzing an achromatic doublet pair lens 10. **Extending Optiland** - [Tutorial 10a - Custom Surface Types](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_10a_Custom_Surface_Types.ipynb) - Adding new surface types - [Tutorial 10b - Custom Coating Types](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_10b_Custom_Coating_Types.ipynb) - Adding new coating types - [Tutorial 10c - Custom Optimization Algorithms](https://github.com/HarrisonKramer/optiland/blob/master/docs/examples/Tutorial_10c_Custom_Optimization_Algorithm.ipynb) - Creating a "random walk optimizer" to optimize an aspheric singlet 11. **Machine Learning in Optical Design** - note that these notebooks are hosted in the [LensAI repository](https://github.com/HarrisonKramer/LensAI) - [Tutorial 11a - Random Forest Regressor to Predict Optimal Lens Properties](https://github.com/HarrisonKramer/LensAI/blob/main/notebooks/Example_1/Singlet_RF_Model_RMS_Spot_Size.ipynb) - Demonstrates how to build and train a random forest regressor to predict the radius of curvature of a plano-convex lens in order to minimize the RMS spot size. - [Tutorial 11b - Ray Path Failure Classification Model](https://github.com/HarrisonKramer/LensAI/blob/main/notebooks/Example_2/Ray_Path_Failure_Classification_Model.ipynb) - Uses logistic regression to predict ray path failures in a Cooke triplet design. - [Tutorial 11c - Surrogate Ray Tracing Model Using Neural Networks](https://github.com/HarrisonKramer/LensAI/blob/main/notebooks/Example_3/Double_Gauss_Surrogate_Model.ipynb) - Builds a neural network surrogate ray tracing model to increase effective "ray tracing" speed by 10,000x. - [Tutorial 11d - Super-Resolution Generative Adversarial Network to Enhance Wavefront Map Data](https://github.com/HarrisonKramer/LensAI/blob/main/notebooks/Example_5/SR_GAN_for_wavefront_data.ipynb) - Utilizes a super-resolution GAN (SRGAN) to upscale low-resolution wavefront data into high-resolution data. - [Tutorial 11e - Optimization of Aspheric Lenses via Reinforcement Learning](https://github.com/HarrisonKramer/LensAI/blob/main/notebooks/Example_4/RL_aspheric_singlet.ipynb) - Reinforcement learning is applied to the optimization of aspheric singlet lenses to generate new lens designs. ## Roadmap Optiland is continually evolving to provide new functionalities for optical design and analysis. Below are some of the planned features and enhancements we aim to implement in future versions: - [ ] **GUI (PySide6-based)** - [ ] **Multi-Path Sequential Ray Tracing** - [ ] **Multiple Configurations (Zoom Lenses)** - [ ] **Thin Film Design and Optimization** - [ ] **Diffractive Optical Elements** - [ ] **Additional Backends: JAX, CuPy** - [ ] **Jones Pupils** - [ ] **Apodization Support** - [ ] **Additional Freeforms (Superconic, etc.)** - [ ] **Image Simulation** - [ ] **Huygens MTF** - [ ] **Interferogram Analysis** - [ ] **Additional Tutorials/Examples** - [ ] **Non-sequential ray tracing** - [ ] **Glass Expert** - [ ] **Insert your idea here...** ### Community Contributions We welcome suggestions for additional features! If there's something you'd like to see in Optiland, feel free to open an issue or discussion. ## License Distributed under the MIT License. See [LICENSE](https://github.com/HarrisonKramer/optiland/blob/master/LICENSE) for more information. ## Contact and Support If you have questions, find a bug, have suggestions for new features, or need help, please [open an issue](https://github.com/HarrisonKramer/optiland/issues) in the GitHub repository. This ensures that your concern is visible to others, can be discussed collaboratively, and helps build a public archive of solutions for similar inquiries in the future. While I prefer issues as the primary means of communication, you may also contact me via email if necessary. Kramer Harrison - [email protected] ", Assign "at most 3 tags" to the expected json: {"id":"13693","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"