The course provides hands on training in computational techniques for physics students. It uses a computational software package (e.g., MATLAB, SciLAB, MathCAD) and a programming language (e.g. V-Python) to aid in the analyses of data and to solve complex systems. Data processing, regression analysis, and simple programming skills will be used to simulate and model conventional physics systems. Visualization techniques will be used to display and interpret data that would have otherwise been too complex for manual analyses. Various topics in physics (e.g., projectile motion, planetary dynamics and oscillating systems) will be analyzed with emphasis on the additional complexity that computational approaches allow the scientist to handle.
Data organization for manipulation:
Functions and Equations:
At the end of the course, students should be able to:
The course assessment will be conducted as follows:
Three graded assignments (PBL) of equal weighting 30%
Two one-hour practical tests (10% each) 20%
One 2-hour final practical examination 50%
Students will be expected to satisfy the examiners in both components.
Giordano, N. J. and Nakanishi, H. (2005), Computational Physics, 2nd Edition; Benjamin Cummings. ISBN-10: 0131469908; ISBN-13: 978-0131469907
Landau, R. H., Paez, M. J. and Bordeianu C. C., (2007), Computational Physics: Problem Solving with Computers, 2nd Edition; Wiley-VCH. ISBN-10: 3527406263; ISBN-13: 978-3527406265