Python code to aid with calculations for nanophotonics. Historically, Py-optics revolves around focused laser beams, with and without a spherical particle. The main modules are (full path lumicks.pyoptics.<module_name>):

• psf: code that calculates the point spread function (electromagnetic field distribution) of a focused laser beam with arbitrary wavefront. The code takes polarization into account and is suitable for high-NA cases.
• trapping: code that calculates
  • The electromagnetic field distribution inside and outside of a spherical particle at an arbitrary distance relative to a focused laser. The laser beam that generates the focus can have an arbitrary wavefront.
  • Forces on the particle.
• farfield_transform: code to transform the near field to the far field.
• field_distributions: electric and magnetic dipole field distributions for dipoles with arbitrary orientation.

Where possible, a multi-threaded implementation, transparently compiled with Numba, is used to speed up numerically-intense parts of a calculation.

All code is developed in-house at LUMICKS. This is alpha-level software: care is taken to verify calculated results against analytical models and/or reference implementations, but no warranties of any kind are given (see also the license).

Py-optics is tested to be compatible with Python version 3.10 to 3.14. However, at the time of writing, free-threading builds are not supported. Py-optics runs on Linux, Windows and MacOS, and is free to use under the conditions of the Apache-2.0 open source license.

1. Create and activate a virtual environment. With conda:

   $ conda create -n py-optics python=3.13
   $ conda activate py-optics
   

2. Clone the repository:

   $ git clone https://github.com/lumicks/py-optics
   $ cd py-optics
   

3. Install the pyoptics package:

   $ pip install -e .
   

   Or, if you want to install the additional dependencies for the example Notebooks:

   $ pip install -e .[examples]
   

   To run the benchmarks, you'll need to install extra packages for testing:

   $ pip install -e . --group dev
   

Example Jupyter Notebooks are available in the examples directory:

4. Run the Notebook:

   $ cd examples
   $ jupyter notebook