The finite-difference time-domain (FDTD) method is a numerical analysis technique used for modeling computational electrodynamics. Python implementations are available for simulating various electromagnetic phenomena.
A Python package for simulating the FDTD algorithm, including examples and documentation for implementing custom simulations. Supports 1D, 2D, and 3D simulations.
Course notes from MIT OpenCourseWare covering numerical methods for electromagnetics, including the FDTD algorithm. Python code examples are provided for illustrating key concepts.
A Python package for simulating the FDTD algorithm, available for installation via pip. Supports simulation of various electromagnetic phenomena, including wave propagation and scattering.
A video tutorial series covering the basics of the FDTD algorithm and its implementation in Python. Topics include grid construction, boundary conditions, and simulation examples.
A research paper from North Carolina State University discussing the application of the FDTD algorithm for simulating electromagnetic phenomena. Python code examples are provided for illustrating key concepts.
Commercial software for simulating the FDTD algorithm, including a Python API for custom simulation and analysis. Supports simulation of various electromagnetic phenomena, including photonics and plasmonics.
A preprint paper discussing a Python implementation of the FDTD algorithm for simulating electromagnetic phenomena. Topics include optimization techniques and parallelization methods for improving simulation performance.