The Finite Difference Time Domain (FDTD) method is a numerical analysis technique used for modeling computational electrodynamics. Implementation in Python using NumPy is a popular approach.
This repository provides a basic implementation of the FDTD algorithm using Python and NumPy. It includes examples and documentation for users to get started with their own simulations.
This paper presents a numerical solution of Maxwell's equations using the FDTD method. The implementation uses Python and NumPy for efficient computation.
This example demonstrates how to implement the FDTD algorithm using NumPy. It provides a step-by-step guide on how to discretize the computational domain and update the fields.
This course covers the fundamentals of the FDTD method and its application in electromagnetic simulations. It includes lectures on implementing the algorithm using Python and NumPy.
This question on Stack Overflow discusses the implementation of the FDTD algorithm in Python. Users have provided answers with example code using NumPy.
This online course covers the basics of computational electromagnetics using the FDTD method. It includes assignments and projects that require implementing the algorithm using Python and NumPy.
This article published in the IEEE journal discusses the use of Python and NumPy for FDTD simulations. It highlights the benefits of using these tools for efficient and accurate computations.