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PHYS 213 Computational Methods in Physics Units: 3.00
Computing environments, algorithms, techniques and programming for solving physics problems. Numerical methods. Code development. Possible topics to be covered include numerical differentiation and integration, root finding and optimization problems, solution of linear systems of equations, Monte Carlo simulation, and symbolic computation.
Learning Hours: 120 (24 Lecture, 24 Tutorial, 72 Private Study)
Requirements: Prerequisite (PHYS 104 or PHYS 106) and (MATH 120 or MATH 121).
Exclusion MATH 272; PHYS 313.
Offering Faculty: Faculty of Arts and Science
Course Learning Outcomes:
- Analyze a physical problem, reducing the problem to study the key factors influencing the evolution of the system, and derive a system of equations to model the behaviour of the resulting system.
- Create, run and analyze the output (graphically and otherwise) of computer programs, in a Python computing environment.
- Design the appropriate computer algorithm to solve the resulting equations and to implement it in well-documented, clearly written code (Python).
- Synthesize the entire process above and create a clear, concise written report summarizing the key results.
- Test the resulting code using known results in simple examples and interpret the results of simulations in more general cases, determining the influence of each parameter affecting the outcome.