Une simulation de l'évolution d'un paquet d'onde gaussien
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Updated
Apr 12, 2018 - Python
Une simulation de l'évolution d'un paquet d'onde gaussien
Fast American option pricing using spectral collocation method based on integral form. An independent Crank Nicolson method is included for comparison.
Finite-Difference Approximations to the Heat Equation. Implementation of schemes: Forward Time, Centered Space; Backward Time, Centered Space; Crank-Nicolson.
This repository contains Python 3 scripts for simulating the passage of a 2D Gaussian wave packet through a double slit. For this, the 2D Schrödinger equation is solved using the Crank-Nicolson numerical method.
A python script that displays an animation of an electron propagation and its interaction with arbitrary potential. The program solves the two-dimensional time-dependant Schrödinger equation using Crank-Nicolson algorithm.
Implementation of well-known numerical methods.
Differents algorithms on python or matlab about numerical analysis - UNI
Beam propagation method (BPM) for photonic integrated circuits (PIC), implemented in MATLAB with finite-differences in 2D. Includes slab waveguide mode-solver.
🚀 Solve the time-dependent Schrodinger equation in unbounded domain
Crank-Nicolson method for the heat equation in 2D
Using Finite Element and Finite Difference Methods to Price European Options
I used the Cranck-Nicholson Algorithm to demonstrate the time evolution of a Gaussian wave by Schrödinger's Picture in Quantum Mechanics. The system is a 1-D box with a positive potential well.
Numerically solved the quantum Hamilton-Jacobi equations of motion and generated trajectories for de Broglie-Bohm theory with recurrent neural networks and the Crank-Nicolson method.
重叠型Schwarz算法利用Crank-Nicolson格式解Fisher-kpp方程
Crank-Nicholson solver for a 1-D heat transfer model.
Finite Difference algorithms for Partial Differential Equation written in python (Based on Smith book)
Python implementation of 1D Time-dependent Schroedinger Equation solver to study the adiabaticity of any 1D system.
Solving problems from the course on the basics of computational physics
Implementation of advanced numerical methods for pricing American options, focusing on the Spectral Collocation and Crank-Nicolson methods. Includes performance analysis in terms of accuracy, stability, and convergence.
This repositary contains the MATLAB implementation of main numerical methods like Newton-Raphson, Simpson's integration and numerical ODE solver.
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