FDTDX
An efficient open-source Python package for 3D photonic nanostructure simulation and design using GPU-accelerated FDTD with automatic differentiation.
What is FDTDX?
FDTDX is an open-source Python package for simulating and designing three-dimensional photonic nanostructures using the Finite-Difference Time-Domain (FDTD) method. It provides GPU-accelerated simulations with built-in automatic differentiation capabilities, enabling efficient gradient-based optimization of complex electromagnetic structures.
Researchers and engineers working in computational photonics, nanophotonics, and electromagnetic simulation who need to optimize complex 3D structures using gradient-based methods.
Developers choose FDTDX for its combination of high-performance GPU acceleration, memory-efficient gradient computation, and automatic differentiation capabilities specifically tailored for large-scale photonic design optimization tasks.
Overview
Electromagnetic FDTD Simulations in JAX
Use Cases
Best For
- Optimizing complex 3D photonic nanostructures using gradient-based methods
- Large-scale electromagnetic simulations requiring billions of grid cells
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