Study-Unit Description

Study-Unit Description


CODE PHY1135

 
TITLE Introduction to Computational Physics

 
LEVEL 01 - Year 1 in Modular Undergraduate Course

 
ECTS CREDITS 6

 
DEPARTMENT Physics

 
DESCRIPTION - Basic computer architecture, binary number system, operating systems;
- Introduction to Python, interactive and batch use of Python;
- Python data types (basic, lists, tuples, dictionaries, sets);
- Control flow (conditionals, loops);
- Functions and recursion;
- File processing;
- Numerical python and plotting (numpy and matplotlib).

The theoretical part of the study-unit will include:
- Determining the roots of an equation using Bisection method, Newton-Raphson and the direct iteration method;
- Solving linear and non-linear system of equations using Gaussian elimination, Jacobi iteration, Gauss-Seidel iteration and Newton-Raphson method in two dimensions;
- Numerical integration using the trapezoidal rule, Simpson’s rule, the Euler’s method;
- Numerical differentiation using backward, forward and central difference formulae for the first and second derivatives;
- Solving first and second order differential equations using Euler's modified method and Runge-kutta;
- Introduction to linear regression.

Study-unit Aims:

The unit seeks to provide an introduction to Phyton as a programming language and will also provide students with mathematical tools to solve analytical problems using numerical methods. It will provide students with the necessary background knowledge to understand and appreciate advanced applications of numerical and computational methods.

Learning Outcomes:

1. Knowledge & Understanding
By the end of the study-unit the student will be able to:

- explain the basic computer architecture, use the logic of writing and debugging a computer program and apply this knowledge to solve scientific problems using numerical methods.

2. Skills
By the end of the study-unit the student will be able to:

- write and debug basic programs in Python;
- apply acquired programming skills to perform data analysis and visualize results;
- determine the roots of an equation using Bisection method, Newton-Raphson and the direct iteration method;
- solve analytical problems using Newton Raphson.

Main Text/s and any supplementary readings:

Textbook:

- Matrelli, Alex. "Python cookbook", 2nd edition, O'Reily, 2005, ISBN 0-596-00797-3

Reference:

- Vermon L. Ceder. "The Quick Python Book", 2nd edition, Manning Publications Co., 2010, ISBN 9781935182207
- Beazley, David M. "Python essential reference", 4th edition, Addison-Wesley, 2009, ISBN 9780672329784
- Python documentation
- Gerald, C.F. and Wheatley, P.O., Applied Numerical Analysis, 7 edition, Pearson Education

 
ADDITIONAL NOTES Pre-Requisite qualifications: Advanced Level Mathematics

 
STUDY-UNIT TYPE Lecture, Practicum & Tutorial

 
METHOD OF ASSESSMENT
Assessment Component/s Assessment Due Resit Availability Weighting
Assignment SEM1 Yes 50%
Examination (1 Hour and 30 Minutes) SEM1 Yes 50%

 
LECTURER/S Alessio Magro
Louis Zammit Mangion

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the study-unit description above applies to the academic year 2019/0, if study-unit is available during this academic year, and may be subject to change in subsequent years.

https://www.um.edu.mt/course/studyunit