This is an introduction to scientific computing in physics. Students will be introduced to computational techniques used in a range of physics research areas. By considering selected physics topics, students will learn computational methods for function analysis, ODEs, PDEs, eigenvalue problems, non-linear equations and Monte Carlo techniques. A physicist's "computational survival toolkit" will also be developed to introduce students to topics such as command line programming, bash scripting, debugging, solution visualization, computational efficiency and accuracy. The course is based on python and will involve working on a set of computational labs throughout the semester as well as a final project.
Any PHY300-level lecture course in Physics. PHY407H1 may be taken in third or fourth year