PHSCS 430
Computational Physics Lab 3
Physics and Astronomy
College of Physical and Mathematical Sciences
Course Description
Computational study of static and dynamic boundary value problems, partial differential equations, linear algebra, and eigenvalues. Applications such as electrostatics, thermodynamics, waves, and quantum mechanics. Computational tools to store, share, and analyze data, including machine learning.
When Taught
Winter
Grade Rule
Grade Rule 8: A, B, C, D, E, I (Standard grade rule)
Min
1
Fixed
1
Fixed
0
Fixed
3
Title
Numerically Solve Partial Differential Equations
Learning Outcome
Write and debug programs to solve physics problems involving partial differential equations.
Title
Linear Algebra
Learning Outcome
Use linear algebra and eigenvalues in the solution of partial differential equations and to find normal modes in mechanical systems.
Title
Data Analysis
Learning Outcome
Use databases to store and share data. Use machine learning tools to model and find patterns in data.
