PHYS 367 - Topics in Scientific Computation

Computational Methods
One-unit semester course. This course focuses on diverse physical problems and computational techniques that can be applied to them, with an emphasis on the mathematical motivation behind the methods. Problems are drawn from electrodynamics, quantum mechanics, classical mechanics, and special and general relativity. The course develops methods for solving ODEs and PDEs and integrating arbitrary functions in multiple dimensions. Numerical linear algebra is covered in both full and iterative form. Additional topics include nonlinear minimization, Galerkin methods, neural network models, and chaotic dynamics.

Unit(s): 1
Group Distribution Requirement(s): Distribution Group III
Prerequisite(s): MATH 201, MATH 202 and PHYS 201, PHYS 202
Instructional Method: Conference
Grading Mode: Letter grading (A-F)
Repeatable for Credit: May be taken 2 times for credit
Not offered: 2023-24
Group Distribution Learning Outcome(s):

Use and evaluate quantitative data or modeling, or use logical/mathematical reasoning to evaluate, test or prove statements.
Given a problem or question, formulate a hypothesis or conjecture, design an experiment, and collect data or use mathematical reasoning to test or validate it.
Collect, interpret, and analyze data.