FDTDX is an efficient open-source Python package for the simulation and design of three-dimensional photonic nanostructures using the Finite-Difference Time-Domain (FDTD) method. Built on JAX, it provides native GPU support and automatic differentiation capabilities, making it ideal for large-scale design tasks.
The key features differentiating FDTDX from other simulation software packages like Meep (which is also great!) are the following:
- High Performance: GPU-accelerated FDTD simulations with multi-GPU scaling capabilities
- Memory Efficient: Leverages time-reversibility in Maxwell's equations for efficient gradient computation
- Automatic Differentiation: Built-in gradient-based optimization for complex 3D structures
- User-Friendly API: Intuitive positioning and sizing of objects in absolute or relative coordinates
- Large-Scale Design: Capable of handling simulations with billions of grid cells
- Open Source: Freely available for research, development and commercial use.
Visit our documentation for:
- Detailed API reference
- Tutorial guides
- Best practices
Also check out our whitepaper for some examples and a comparison to other popular FDTD-frameworks.
Install FDTDX using pip:
pip install fdtdx # Basic CPU-Installation
pip install fdtdx[cuda12] # GPU-Acceleration (Highly Recommended!)
pip install fdtdx[rocm] # AMD-GPU (only python<=3.12)For development installation, see the contributing guidelines!
# The following lines often lead to better memory usage in JAX
# when using multiple GPU.
export XLA_PYTHON_CLIENT_ALLOCATOR="platform"
export XLA_PYTHON_CLIENT_PREALLOCATE="false"
export NCCL_LL128_BUFFSIZE="-2"
export NCCL_LL_BUFFSIZE="-2"
export NCCL_PROTO="SIMPLE,LL,LL128"If you find this repository helpful for you work, please consider citing:
@article{Mahlau2026,
doi = {10.21105/joss.08912},
url = {https://doi.org/10.21105/joss.08912},
year = {2026},
publisher = {The Open Journal},
volume = {11},
number = {117},
pages = {8912},
author = {Mahlau, Yannik and Schubert, Frederik and Berg, Lukas and Rosenhahn, Bodo},
title = {FDTDX: High-Performance Open-Source FDTD Simulation with Automatic Differentiation},
journal = {Journal of Open Source Software}
}
This project was developed at the Institute of Information Processing at Leibniz University Hannover, Germany and sponsored by the cluster of excellence PhoenixD (Photonics, Optics, Engineering, Innovation across Disciplines).