Numerical methods for solving problems in mechanics, astrophysics, electromagnetism, quantum mechanics, and statistical mechanics. Methods include numerical integration; solutions of ordinary and partial differential equations; solutions of the diffusion equation, Laplace's equation, and Poisson's equation with various methods; statistical methods including Monte Carlo techniques; matrix methods and eigenvalue problems. A short introduction to Python, which is used for class examples and active learning notebooks. Independent class projects allow deep explorations of course topics and make up a significant component of the course grade. No prerequisites but some previous programming experience is advisable.
4 units · Letter or Credit/No Credit · GER: WAY-AQR, WAY-FR
Numerical methods for solving problems in mechanics, astrophysics, electromagnetism, quantum mechanics, and statistical mechanics. Methods include numerical integration; solutions of ordinary and partial differential equations; solutions of the diffusion equation, Laplace's equation, and Poisson's equation with various methods; statistical methods including Monte Carlo techniques; matrix methods and eigenvalue problems. A short introduction to Python, which is used for class examples and active learning notebooks. Independent class projects allow deep explorations of course topics and make up a significant component of the course grade. No prerequisites but some previous programming experience is advisable.
Offered in Spring 2026 at Stanford University.