Computational Physics Track

Computational Physics has become an essential approach to physics, both for data analysis and for exact solutions of theoretical models that are not analytically solvable.  Thus, computational skills are valuable for physicists pursuing either a theoretical or experimental focus.  The computational physics track encourages students to develop essential programming skills along with the algorithmic methods commonly used in different areas of physics.

Students should complete the physics gateway, core, and lab requirements as described in the physics track.

Electives:

Up to 2 elective credits can come from outside Physics.  Suggested electives are listed below.  Due to yearly changes in course availability, there may be courses not listed below that are appropriate as an elective. Consult with your Physics advisor if you wish to consider other non-physics courses as an elective.

Suggested Physics Electives:

PHYS 217 Nonlinear Dynamics and Chaos
PHYS 313 Classical Dynamics
PHYS 315 Quantum Mechanics II
PHYS 340 Computational Physics, either as lab or elective credit
PHYS 565 Mathematical Physics

Suggested Non-Physics Electives:

ASTR 210 Fundamentals of Scientific Computing in Astronomy
CHEM 396 Molecular Modeling and Design
COMP 211 Computer Science I
COMP 212 Computer Science II
COMP 333 Software Engineering
COMP 353 Robotics
IDEA 350 Computational Media:  Videogame Development (only counts toward one elective credit)
QAC 241 Introduction to Network Analysis
QAC 312 Hierarchical Linear Models
QAC 356 Advanced R: Building Open-Source Tools for Data Science
QAC 385 Applications of Machine Learning in Data Analysis