PHY2039 : Scientific Computation with Python
- Offered for Year: 2025/26
- Module Leader(s): Dr Chris Graham
- Co-Module Leader: Professor Jon Goss
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
Aims
To reinforce the computing in Python studied as part of physics laboratories at Stage 1, and to provide the foundations for candidates to undertake independent programming activities.
To introduce a range of mathematical techniques relevant to physical problems using Python, including methods that will be useful towards project work elsewhere in the programme.
Module Summary
Computing methods are of great use in a wide range of applications in physics. This module builds on the methods introduced at Stage 1, introducing additional techniques, some of increasing computational sophistication, with broad applications in a physics context. In implementing these methods, students will attain an increased competence with Python programming, and an increasing ability to use such methods independently, towards project-orientated goals. The module supports the development of a range of transferable skills including problem solving, computer literacy, data analysis and presentation.
Outline Of Syllabus
The module covers a range of computational strategies including:
- Reading, querying and manipulating data, such as working with formats regularly used for physics research.
- Data visualisation and plotting, such as plots in 2D and 3D and production of high-quality academic plots.
- Arrays and matrices in Python, including linear algebra techniques such as required for solving eigenvalue problems.
- Curve fitting, building on the foundations established at stage 1.
- Numerical approaches to root finding.
- Numerical derivatives through finite difference, and related techniques of numerical integration.
- Numerical solution of ordinary differential equations and applications to physical systems.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 7 | 1:00 | 7:00 | Problem Classes |
| Guided Independent Study | Assessment preparation and completion | 20 | 1:00 | 20:00 | Completion of in course assessment |
| Scheduled Learning And Teaching Activities | Lecture | 4 | 1:00 | 4:00 | Lectures |
| Scheduled Learning And Teaching Activities | Lecture | 11 | 2:00 | 22:00 | Computer Practicals |
| Guided Independent Study | Assessment preparation and completion | 15 | 1:00 | 15:00 | Exam preparation, revision and completion of examination. |
| Guided Independent Study | Independent study | 32 | 1:00 | 32:00 | Preparation time for lectures, background reading, coursework review |
| Total | 100:00 |
Teaching Rationale And Relationship
Lectures and problem classes are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Practicals are used to help develop the students’ abilities at applying the theory to solving problems.
The teaching methods are appropriate to allow students to develop a wide range of skills, from understanding basic concepts and facts to higher-order thinking.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Digital Examination | 120 | 1 | A | 60 | Digital Examination - in person |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Prob solv exercises | 1 | M | 40 | Problem-solving exercises assessment |
Assessment Rationale And Relationship
A substantial examination is appropriate for the assessment of the material in this module. The format of the examination will enable students to reliably demonstrate their own knowledge, understanding and application of learning outcomes. The assurance of academic integrity forms a necessary part of the programme accreditation.
The coursework assignment allows the students to develop their problem-solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; this assessment has a secondary formative purpose as well as a primary summative purpose.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- PHY2039's Timetable