Diffinytrace Documentation

DiffinyTrace is a Python library for differentiable ray tracing and optical system optimization using PyTorch. It enables automatic differentiation through optical systems, making it possible to optimize lens designs, mirror configurations, and other optical components using gradient-based methods.

The source code is available at the GitHub repository.

Key Features

Transformation example

Flexible Transformations — apply general transformations such as rotations and translations to optical components, with full control over the parameters and their role in the transformation.

CAD export example

Seamless CAD Export — generate lenses and mirrors that can be exported to standard CAD file formats.

B-spline surface example

Freeform Surfaces — design complex optical elements with advanced B-spline representations for maximum flexibility.

  • Differentiable Ray Tracing: Full automatic differentiation support through optical systems

  • Constraint Optimization: Advanced optimization with PyTorch and SciPy integration

  • Illumination Design: Algorithms for computing lens surfaces to achieve desired illumination profiles

  • GPU Acceleration: CUDA support for high-performance computations

Installation

  1. Create a new Environment via conda:

    conda create -n dit python==3.12

    Activate the environment via:

    conda activate dit

    Install pip:

    conda install pip

  2. Install PyTorch

    Check your CUDA version with:

    nvcc --version

    DiffinyTrace has only been tested with 2.10.0+cu130. Make sure to install the appropriate version of PyTorch for your system. You can find the installation instructions on the PyTorch website. DiffinyTrace should work for both CPU and CUDA versions.

  3. Install DiffinyTrace

    Install all other dependencies and the library itself via:

    pip install diffinytrace

    Or directly in the folder via:

    pip install -r requirements.txt

Basic Usage Example

import diffinytrace as dit
import torch
NBK7 = dit.materials["NBK7"]

wave_len = 1.024
light_transform = dit.transforms.Offset(torch.tensor([0.0,0.0,0.0]))
source = dit.source.CollimatedMonochromatic(light_transform,8.0,wave_len)

plane_surface = dit.Plane()
surface2 = dit.Aspheric(-1/50.)
transf1 = dit.transforms.Distance(10.0,parent_transform=source)
lens1 = dit.Lens(transf1,5.,plane_surface,surface2,NBK7,13.0)
transf2 = dit.transforms.Distance(15.0,parent_transform=lens1)
detector = dit.Detector(transf2,plane_surface,8.0)
system = dit.SequentialOpticalSystem({"source":source, "lens":lens1, "detector":detector})
#dit.plotting.system3D.plot(system,resolution=10)
x,weights = source.sample(10)
O,D,wave_len,_,meta_data = system(x,["source","lens","detector"])
dit.plotting.system2D.plot(system,meta_data)

Documentation Structure

Contents

License

DiffinyTrace is licensed under the MIT License. See the repository for full license details.