Undergraduate Course: Numerical Recipes (PHYS10090)
Course Outline
| School | School of Physics and Astronomy |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The main aim of this course is to develop an understanding of how numerical computations are implemented in practice. It will introduce the simplest ways to implement functionality and then show how to achieve the same using library packages. |
| Course description |
This course is taught through a combination of hands- on programming exercises in the CPLab. Python will be used as the programming language for this course. Proficiency in Python is assumed (this is not a Python programming course).
The course material will include:
- Linear algebra (solving linear systems of equations, diagonalization)
- Minimisation methods
- Parameter fitting to data sets (Chi squared, maximum likelihood, Bayesian
inference)
- Random number generation
- Root finding
- Monte Carlo methods
- Integration
- Differential equations (ordinary and partial)
- Discrete Fourier Transform
- Principles of machine learning
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Computer Simulation (PHYS08026) OR
Computer Modelling (PHYS09057)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | Proficiency in Python.
Students must be able to prove proficiency in Python and use of a Unix environment.
|
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2019/20, Available to all students (SV1)
|
Quota: 101 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 30,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
58 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
The course will be 100% assessed through coursework consisting of three checkpoints (solutions handed in after the end of a block of 3-4 labs). |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
- Implement simple versions of standard numerical algorithms in a computer pro-gram
- Implement the same functionality using widely available numerical library packages
- To gain a practical grounding in how to deal with dealing with and analyzing data which arises in a real physics research environment.
- Resolve conceptual and technical difficulties by locating and integrating relevant information from a diverse range of sources
|
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
Lectures for first hour during weeks 1-10 Laboratory sessions of 3 hours during weeks 2-11 |
| Keywords | NRec |
Contacts
| Course organiser | Dr Bartlomiej Waclaw
Tel: (0131 6)51 7688
Email: bwaclaw@staffmail.ed.ac.uk |
Course secretary | Miss Denise Fernandes Do Couto
Tel: (0131 6)51 7521
Email: Denise.Couto@ed.ac.uk |
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