ZCE 111/4 Computational Physics
Synopsis
The course aims
at training physics students to use computer to solve realistic physics
problems and to provide them with tools and knowledge they can utilize
throughout their career in the future. The students shall acquire some
ideas of
what is possible with computers and what type of tools are available
for
computing real physics problems. This course covers some of the basics
of
computation, numerical analysis, and programming from a computational
science
point of view. This will be a practical
course focused on application of mathematics and physics using computer
rahter
than an introductory programming or computer science, with minimal
discussion
of computer science theory.
Learning
Ourcome
At the end of the course, students will
1) show proficiency in programming and using mathematical packages
2) be able to use computer software to visualise physics formulae
3) be able to use computer software to solve fairly complex physics problems
4) be able to write codes to solve numerical problems
Main
textbook
Computational Physics, 2/E
Author: Nicholas J. Giordano, Hisao Nakanishi
Publisher: Addison-Wesley
Published:
07/21/2005
Mathematica Reference
Mathematica Documentation Center
Other References
1. A First Course in Scientific Computing: Symbolic, Graphic, and Numeric Modeling Using Maple, Java, Mathematica, and Fortran90
Author: Rubin H. Landau. Publisher: Princeton University Press (April 11, 2005)
2.
Computational Physics: Problem Solving
with Computers by Rubin
H. Landau, Manuel J. Páez, and Cristian C. Bordeianu
(Paperback
- Sep 21, 2007)
3. An Introduction to Computational Physics, by Tao Pang, Cambridge University Press; 2 edition (February 13, 2006)
Lecture-by-lecture
schedule
|
Lecture and tutorial |
Topics |
Contact hours |
|
Week
1 |
Root finding and optimization |
4 h |
|
Week
2 |
Fitting data to a function |
4 h |
|
Week
3 |
Numerical integration |
4 h |
|
Week
4 |
Visualizing of data |
4 h |
|
Week
5 |
Matrix operation and manipulation |
4 h |
|
Week
6 Week
7 |
Monte Carlo applications |
8 h |
|
Week
8 |
Solving eigen value problem numerically |
8 h |
|
Week
9 Week
10 |
Solving ordinary differential equations numerically |
8 h |
|
Week
11 Week
12 |
Finite difference method |
8 h |
|
Week
13 Week
14 |
Project |
8 h |
|
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Total |
56 |
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