Undergraduate Course: Numerical Recipes (PHYS10090)
|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
|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. There will be significant hands-on programming in Python.
Students may elect to use C++ if they are proficient).
This course is taught through a combination of hands- on programming exercises in the CPLab.
At present students may elect to use Python or C++ subject to the agreement of the course organiser.
The course material will include:
- Matrices and matrix manipulation
- Minimisation methods
- Parameter fitting to data sets ( Chi squared and maximum likelihood)
- Random number generation, non uniform distributions
- Monte Carlo data set generation
- Simulation and analysis of a muon decay lifetime experiment
- Discrete fourier transforms
- Machine Learning
- Other numerical topics
Entry Requirements (not applicable to Visiting Students)
|| Students MUST have passed:
Computer Simulation (PHYS08026) OR
Computer Modelling (PHYS09057)
||Other requirements|| Proficiency in Python.
Students must be able to prove proficiency in Python and use of a Unix environment.
Information for Visiting Students
|High Demand Course?
Course Delivery Information
|Academic year 2017/18, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 33,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||The course will be 100% assessed through coursework consisting:
1. Checkpoints during the workshop sessions
2. Hand In reports
|No Exam Information
| - 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
|Graduate Attributes and Skills
|Additional Class Delivery Information
||Lectures for first hour during first 6-7 weeks.
Laboratory sessions of 3 hours throughout semester
|Course organiser||Prof Peter Clarke
|Course secretary||Miss Yolanda Zapata-Perez
Tel: (0131 6)51 7067