Brief Syllabus:

Introduction to computer software used in Physics; the C programming language; integers/floating-point numbers; the Mandelbrot set; generating and using random numbers; plotting; numerical integration techniques; many-body gravitation; cellular automata; Wolfram’s A New Kind of Science; Conway’s Game of Life; subtleties in apparently simple algorithms; analysis of experimental data. Numerical techniques for the solution of non-linear equations, for polynomial interpolation, numerical integration, ordinary differential equations and for waves.

Assumed Knowledge:

From the 2003 Undergraduate Handbook, the prerequisites are: PHYS1002 or PHYS1022 or PHYS1221 or PHYS1231 or PHYS1241 and MATH1021 or MATH1231 or MATH1241 or MATH1031. Excluded: PHYS2001.

No computer programming knowledge in C is assumed. We will assume that you have a knowledge of Maple and Linux, as taught in the Mathematics prerequisites.

Course Goals:

The main aim of the course is to teach you how to program a computer in order to be able to solve a wide range of problems in Physics.

The first part of the course will be used to teach you the elements of the C programming language. C has been chosen since (1) it is freely available, (2) it is commonly used, and (3) the basic concepts used in C are common to many other programming languages.

The remaining lectures will show how your programming knowledge can be used to attack a variety of interesting physics problems.

Learning Objectives

You will learn techniques required to write reliable, efficient, software. This is not easy, and you will learn that even simple problems, such as finding the roots of a quadratic equation, or calculating the standard deviation of a data set, can be surprisingly subtle.

You will have a strong foundation for picking up other programming languages and packages during your career.

Why is computational physics important?

Computers are one of the most powerful tools available to the physicist.  They are used in all areas of physics: ranging from theoretical calculations using supercomputers, analysing terabytes of data, to controlling instrumentation.  There has even been speculation that the universe itself is effectively a computer.

A knowledge of how to use computers is invaluable to all scientists.

How to succeed - Strategies for Learning

The only way to learn a computer programming language is to practice programming, at least weekly. PHYS2020 is one course where you can not cram the day before the exam and expect to pass. To assist with this learning process, you will be expected to complete a series of six assignments. Additionally a number of tutorial questions will also be set.

It is the nature of programming that the time required to solve a problem is difficult to predict.  You may find that you can complete one assignment in 30 minutes, whereas the following week you may spend three hours trying to track down a problem that turns out to be a missing semicolon.  As you gain more experience, this unpredictability will be reduced, and your enjoyment will be increased.

While some course notes will be available on the web, it is vital to turn up to the lectures.