maxwell-equations

fdtd3d is an open source 1D, 2D, 3D FDTD electromagnetics solver with MPI, OpenMP and CUDA support for x64, ARM, ARM64, RISC-V, PowerPC, Wasm architectures

PyPEEC - 3D Quasi-Magnetostatic FFT/PEEC Solver

Photonic crystals in Julia 🦚

An nanophotonics solver for inverse design of metamaterials

Time Domain Maxwell Solver

Full-wave 3D electromagnetic field simulation in Python

An FDFD electromagnetic mode solver for rasterized waveguide cross sections made to be a standard plugin for FDTD engines.

2D FDTD solver of Maxwell's equations

My lectures for the University of Liverpool PHYS201 (Electromagnetism I) module

Python/C++ electromagnetic simulator for photonic devices using the finite-difference time-domain (FDTD) method.

Lecture Notes in Electromagnetics II for Engineering Physics master students at Uppsala University (2022-2026)

Official implementation of STAR-PINN: a Physics-Informed Neural Network (PINN) for solving the 2D time-domain magnetic diffusion (Maxwell) equation in nonlinear materials.

A self-contained 2D finite-element electrostatics solver for simulating real capacitor geometries — parallel plates, coaxial cables, and arbitrary shapes built from simple primitives — rather than relying on closed-form formulas that only exist for a handful of idealized geometries. Pure NumPy / SciPy / Matplotlib.

Solving the Eddy Current problem with a multiplicative Schwarz smoothed geometric multigrid preconditioned GMRES solver in deal.II.

AI-assisted electromagnetic cavity eigenmode simulator with deterministic Maxwell/Nedelec FEM, natural-language orchestration, C++17/Python, Gmsh and PETSc/SLEPc

Finite-difference time-domain (FDTD) method for modeling computational electrodynamics

Physics-informed neural network solving Maxwell's equations in ICP reactors. Hard BC ansatz, transfer learning across geometries, autograd sensitivity maps. 1700× faster than FEM. Built with NVIDIA Modulus + PyTorch.

Explore computational physics in Threejs VR

FEniCS programs for solving Maxwell's equations in some special cases

FELINES is a predictive lightning protection system that detects Preliminary Breakdown Pulses (PBP) to forecast dangerous Return Strokes (RS) affecting electrical infrastructures. Combining electromagnetic modeling, and machine learning enables the preventive disconnection of vulnerable power and renewable energy systems before damage occurs.