Numerical Techniques for Physicists

Cod y Modiwl: PH26600
Teitl y Modiwl: Numerical Techniques for Physicists
Blwyddyn Academaidd: 2026/2027
Semester: Semester 1 Dysgwyd dros 2 semester
Cyd-gysylltydd y Modiwl: Dr Tom Knight
Rhestr Ddarllen: Gweld ar Aspire
Rhagofynion: MP10610 neu MT10610
Rhagofynion: FG16210
Anghymharus (Unrhyw Flwyddyn Acad): MA25220
Anghymharus (Unrhyw Flwyddyn Acad): PH26510
Anghymharus (Unrhyw Flwyddyn Acad)
Anghymharus (Unrhyw Flwyddyn Acad)
Anghymharus (Unrhyw Flwyddyn Acad): MT25220
Staff Eraill sy'n Cyfrannu: Dr Balazs Pinter

Dulliau Asesu

Math o Asesiad	Manylion Asesiad	Cyfran
Asesiad Semester	Technique application, in-class:	20%
Asesiad Semester	Online task,: in-class	20%
Asesiad Semester	Written report,: 1500 words	30%
Asesiad Semester	Online coding test, in-class x 2:	30%
Asesiad Ailsefyll	As determined by the Departmental Examination Board:	100%

Canlyniadau Dysgu

Wedi cwblhau'r modiwl dylai'r myfyrwyr fedru:

1. Construct small programs and visualisations in Python, with an awareness of good practice in developing code. 2. Recognise when binomial, Poisson, uniform, or Gaussian distribution describes data, and calculate their mean, standard deviation, and other expectation values. 3. Develop computer programs for various techniques for scientific computing and analysis. 4. Inspect a range of numerical methods. 5. Examine and numerically solve problems described by Ordinary Differential Equations.

Disgrifiad cryno

There are numerous mathematical problems that are either impractical or impossible to solve analytically and must instead be solved by computers using numerical techniques. Mathematical techniques are essential to Physics and, therefore, so are such numerical techniques. In Semester 1 this module introduces Python in the broader context of the Scientific Python Stack (Scientific Libraries/Extensions to the core Python language) and statistics. Following the introduction, in Semester 2, this module continues to introduce methods for numerical analysis, and modelling. Application of these techniques will be achieved through practical workshops.

Cynnwys

Semester 1

• Types and variables in Python

• Data structures: Lists, dictionaries and NumPy arrays

• Control Statements and Blocks: If-statements, for- and while-loop

• Organising Python code:
- Function definition and calling
- Catching and handling exceptions
- Organising code into modules

• File handling and data formats

• Visualising data (plotting) and data manipulation

• Statistics, including:
- Gaussian, Poisson and binomial distributions
- Hypothesis Testing

Semester 2

• Numerical Analysis, including:
- Regression (Linear and Curve Fitting)
- Integration
- Root Finding
- Interpolation
- Fourier analysis

• ODE Solving, including:
- Euler’s and Runge-Kutta Methods
- Application to chaotic systems

Sgiliau Modiwl

Math o Sgiliau	Manylion Sgiliau
Cyfathrebu	Written Report, Documenting Code.
Datblygu personol a chynllunio gyrfa	No, though skills taught are in high demand from employers.
Datrys Problemau	Problem solving skills are required and developed throughout the module.
Gwella dysgu a pherfformiad ei hun	From feedback (automatic, through computer, and in-practical feedback from demonstrators and staff).
Rhifedd	The application of number is required throughout the module.
Sgiliau pwnc penodol	Programming, debugging, statistical, data analysis and modelling skills.
Sgiliau ymchwil	Using a computer. Searching the language and library documentation.
Technoleg Gwybodaeth	Application of IT skills are central throughout the module.

Nodau

Mae'r modiwl hwn yn cydymffurfio a FfCChC Lefel 5