The FDTD method is a numerical analysis technique used for modeling computational electrodynamics. This example demonstrates how to implement the FDTD algorithm using NumPy for solving Maxwell's equations in one dimension.
A Python implementation of the Finite-Difference Time-Domain (FDTD) method using NumPy for solving electromagnetic wave propagation problems. The code includes a 1D and 2D implementation with example use cases.
This paper presents a Python implementation of the FDTD algorithm using NumPy for simulating electromagnetic wave propagation in various media. The code is optimized for performance and includes example simulations.
This article describes a NumPy-based FDTD solver for electromagnetic simulations, including a discussion on the numerical implementation, boundary conditions, and example simulations.
The Finite Difference Time Domain (FDTD) method is a numerical analysis technique used for modeling computational electrodynamics. This article provides an overview of the FDTD method, including its history, theory, and applications.
This video tutorial demonstrates how to implement the FDTD algorithm in Python using NumPy, including a step-by-step explanation of the code and example simulations.
This documentation provides an overview of using NumPy and SciPy for scientific computing, including a discussion on the FDTD method and its implementation using these libraries.
A Python package for simulating electromagnetic wave propagation using the FDTD method. The package includes a simple and efficient implementation of the FDTD algorithm using NumPy.