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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

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DRPS : Course Catalogue : School of Physics and Astronomy : Undergraduate (School of Physics and Astronomy)

Undergraduate Course: Numerical Recipes (PHYS10090)

Course Outline
SchoolSchool of Physics and Astronomy CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThe aim of this course is to develop an understanding of numerical algorithms, how they are implemented, and how to use them to solve practical numerical problems using standard Python libraries such as SciPy.
Course description This course is taught through a combination of lectures and hands- on programming exercises. 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)
- Optimization (finding minima and maxima of real-valued functions)
- Parameter fitting to data sets (Chi squared, maximum likelihood, Bayesian
inference)
- Random number generation
- Non-linear 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-requisitesNone
High Demand Course? Yes
Course Delivery Information
Academic year 2022/23, Available to all students (SV1) Quota:  116
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) 100% coursework assessed 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
On completion of this course, the student will be able to:
  1. Implement simple versions of standard numerical algorithms in a computer program
  2. Implement the same functionality using widely available numerical library packages
  3. To gain a practical grounding in how to deal with typical numerical problems that arise in a real physics research environment
  4. Resolve conceptual and technical difficulties by locating and integrating relevant information from a diverse range of sources
Reading List
None
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
KeywordsNRec
Contacts
Course organiserDr Sergey Koposov
Tel:
Email: Sergey.Koposov@ed.ac.uk
Course secretaryMrs Ola Soldan-Kieliszek
Tel: (0131 6)51 3448
Email: Ola.Soldan@ed.ac.uk
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