Overview
Syllabus
Euler Method (with python notebooks).
PH 280/Project 1.
Heun Method (fixed audio).
TaylorSeries: Approximating the Morse Potential.
pylab sympy together.
RK4 and Symplectic Methods of Integration.
Monte Carlo: Demon Algorithm.
The Drunken Sailor Problem with Numpy/Jupyter Notebook. (fixed!).
matrix methods: Optics with matrices.
Power Laws and Fitting Data with Matrices.
Numerical Integration: Large Amplitude Pendulum.
Root Finding: Energy Eigenstates.
Coupled Oscillators.
Project 12, The Perceptron: Intro to Supervised Machine Learning.
FFT Fun: Complex Numbers, Discrete Fourier Transforms.
Taylor Series in Scientific Computing.
Geometrical Optics.
Fitting Pendulum data with curve_fit.
Stochastic matrix as an Eigenvector application.
Coupled Oscillators as an application of Eigenvectors.
Fourier Series with basis functions.
Google Colab Setup.
Taught by
Steve Spicklemire