Side by side
FDTDX vs PyAutoLens
Both stand on physics simulation software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan LinuxSelf-hosted
FDTDX provides a JAX-based workflow for photonic nanostructure simulation and optimization, with GPU support and GDS-related API functions. Its FAQ warns that the relatively new project may still have bugs.
Visit FDTDX Free plan LinuxMacWindows
Choose PyAutoLens if you need a free, offline package for detailed gravitational-lensing analysis across imaging, interferometer or point-source data. Allow for its Python version requirement, and check the installation path for your operating system and hardware, especially if you need GPU acceleration.
Visit PyAutoLensThe facts
| FDTDX | PyAutoLens | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Linux, Self-hosted | Linux, Mac, Windows |
| Lowest paid plan | Free or on request | Free or on request |
| Plans published | 1 | 1 |
| Maker | Not published | Not published |
| Website | fdtdx.readthedocs.io | pyautolens.readthedocs.io |
| On physics simulation software | #21 of 89 | #25 of 89 |
FDTDX: what it does well
- Free for research, development, and commercial use.
- Supports automatic differentiation and gradient-based optimization.
- Offers GPU acceleration and multi-GPU scaling.
- API includes GDS polygon and layer-stack functions.
- Documentation includes Jupyter quickstarts and physics tutorials.
What to know first
- The FAQ notes that bugs may occur.
- Listed platforms are Linux and self-hosted.
- The project describes itself as relatively new.
PyAutoLens: what it does well
- Free package with offline access and data export.
- Models galaxy-, group- and cluster-scale lens systems.
- Reconstructs irregular source galaxies using pixelized models.
- Fits spectral-line data cubes across all channels with a shared lens model.
- Supports imaging, interferometer and point-source observations.
What to know first
- Requires Python 3.12 or later.
- Windows installation requires Anaconda.
- GPU acceleration requires a separate JAX installation.
- Intel Macs use the slower NumPy path.
Alternatives to FDTDX Alternatives to PyAutoLens The whole list