University of St Andrews

Key information

SCOTCAT credits : 10

ECTS credits : 5

Level : SCQF level 9

Semester: 1

This module is designed to develop a level of competence in Python, a modern programming language currently used in many physics research labs for mathematical modelling. No prior experience is required. The module starts with a grounding in the use of Python and discusses numerical methods. The main focus is then on the ways in which Python can be used for problem solving in physics and astrophysics.

Relationship to other modules

Pre-requisite(s): Before taking this module you must pass PH2012 and ( pass MT2501 and pass MT2503 )

Anti-requisite(s): You cannot take this module if you take PH3082

Learning and teaching methods and delivery

Weekly contact: 2hr lab x 10 weeks, 2 x 1hr lecture with Q&A x 10 weeks

Scheduled learning hours: 40

Guided independent study hours: 60

Assessment pattern

As used by St Andrews: 3-hour Computer-based Examination = 75%, continual assessment = 25%


Re-assessment: Oral Re-assessment, capped at grade 7

Personnel

Additional information from school

Aims & Objectives

To experience how numerical modelling is used to explore physical concepts.

To develop a level of expertise in modelling physical problems and to introduce common solving and visualising techniques.

Data analysis to extract physical information from measured data and images.

Solving differential equations numerically.

Learning Outcomes

The students will be able to program in Python, and be able to use Python to solve, visualise and gain insight into a variety of physical problems.

Synopsis

There are introductory exercises teaching basic programming skills in Python, different numerical methods and setting up physical problems. We work through case studies designed to illustrate the use of programming to solve and visualise a variety of physics problems. The case studies can vary from year to year. Past case studies have included: simulating the motion of the planets in the solar system, geometric optics, elastic waves and thermodynamics.

Numerical techniques used in this module include:

• Root finding
• Studies involving one and two parameters
• Model fitting
• Parameter optimisation / determining stability regions
• Numerical differentiation
• Numerical integration
• Solving systems of ordinary differential equations

Indicative timetable: weeks 1-2: introduction, weeks 3-5 and 7-11: case studies, each week there will be the opportunity to engage with teaching staff both in-person and online. Indicative deadlines:

Indicative deadlines: Engagement questions: Monday weeks 2-5, and 7-11,

Forum posts: Monday week 7 and Friday week 11.

Additional information on continuous assessment, etc.

The continuous assessment takes the form of forum interactions in Moodle, and engagement questions.

Recommended Books

Please view University online record:

https://sta.rl.talis.com/index.html