The FDTD method is a numerical analysis technique used for solving partial differential equations. This example demonstrates how to implement the FDTD method using NumPy for solving the 1D wave equation.
This GitHub repository provides an example implementation of the FDTD method using Python and NumPy for solving the 2D wave equation. The code includes a detailed explanation and example use cases.
This research article presents a numerical solution of Maxwell's equations using the FDTD method and NumPy. The authors demonstrate the accuracy and efficiency of the proposed method for solving electromagnetic problems.
This preprint presents an application of the FDTD method for solving the time-dependent Schrödinger equation using NumPy. The authors discuss the numerical stability and accuracy of the proposed method.
This video tutorial demonstrates how to perform FDTD simulations using NumPy and Matplotlib. The author provides a step-by-step guide on implementing the FDTD method for solving the 1D wave equation.
This article provides a comprehensive guide on implementing the FDTD method in Python using NumPy. The author includes example code and explanations for solving the 1D and 2D wave equations.
This conference paper presents a NumPy-based FDTD solver for electromagnetic simulations. The authors discuss the performance and accuracy of the proposed solver for solving large-scale electromagnetic problems.
This online course provides a tutorial on the FDTD method using NumPy. The course covers the basics of the FDTD method, implementation in Python, and example applications in electromagnetics and photonics.