Introductory description

This module develops programming in the Python programming language and follows from PX150 Physics Programming Workshop

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Handling, processing and analysing physics data: plotting distributions, least square and
   maximum likelihood fit.
2. Monte Carlo simulation for physics modelling. Different types of random numbers, quality of
   random number generators. Generation of random numbers according to specific distributions.
   Brownian motion and diffusion.
3. Numerical integration and differentiation. Mass and centre of mass of object with variable
   density. Electric fields generated by distributed charge.
4. Numerical solutions of ordinary differential equations. Mechanical oscillations, motion with
   resistance.

Learning outcomes

By the end of the module, students should be able to:

• Explain how computers can be used to solve physics problems
• Translate physics problems into a form suitable for implementing in computer program
• Design algorithms and implement them.
• Handle and analyse physics data

Indicative reading list

M. Newman, Computational Physics, CreateSpace Independent Publishing Platform, ISBN: 978-
1480145511 (2012).

• H.P. Langtangen, A Primer on scientific programming with Python, Springer e-books (2012):
  http://link.springer.com/book/10.1007%2F978-3-642-18366-9

• Python documentation: http://www.python.org/doc/

• Scientific Python: http://docs.scipy.org/doc/scipy/reference/

Subject specific skills

Knowledge of programming. Skills in numerical modelling.

Transferable skills

IT skills, analytical, communication, problem-solving, self-study