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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014
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DRPS : Course Catalogue : School of Physics and Astronomy : Undergraduate (School of Physics and Astronomy)

Undergraduate Course: Advanced Computer Simulation (PHYS10014)

Course Outline
SchoolSchool of Physics and Astronomy CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) Credits10
Home subject areaUndergraduate (School of Physics and Astronomy) Other subject areaNone
Course website https://www2.ph.ed.ac.uk/internal/coursework/wwwcoursework/csim3/ Taught in Gaelic?No
Course descriptionThis is a practical course which develops the techniques of computer simulation in physics through the exploration of specific examples. It consists of an introduction to Monte Carlo integration, a study of the numerical integration of simple dynamical systems, and a look at some non-numerical computational methods for computer symbolic algebra. The course is taught through a series of two-hour supervised practical classes in the Computational Physics Laboratory. The course is continuously assessed: there is no Degree Examination.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Computer Simulation (PHYS08026) OR Computational Methods (PHYS09016)
Students MUST have passed:
Co-requisites
Prohibited Combinations Other requirements Prior Java experience is essential.
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Not being delivered
Summary of Intended Learning Outcomes
After completing this course students should:
1) be familiar with the properties of floating point arithmetic, rounding errors, errors due to algorithmic
approximations, basic (Euler)numerical integration methods and simple higher-order integrators (leapfrog);
2) have learnt about the principles of Monte Carlo integration, including importance sampling, simple
methods of generating pseudo random numbers for specified distributions, but not Markov Chain methods;
3) have an understanding of the techniques used to implement computer algebra systems, including the use of
recursion, linked lists, garbage collection, and markup languages such as MathML;
4) have a deeper understanding of the utility and
limitations of derived classes, interfaces, and inheritance in object-oriented programming languages (specifically Java);
5) be familiar with the use of documentation generator tools (specifically JavaDoc).
Assessment Information
3 items of coursework, 100%
Visiting Student Variant Assessment
3 items of coursework, 100%
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsACSim
Contacts
Course organiserProf Anthony Kennedy
Tel: (0131 6)50 5272
Email: Tony.Kennedy@ed.ac.uk
Course secretaryMiss Jillian Bainbridge
Tel: (0131 6)50 7218
Email: J.Bainbridge@ed.ac.uk
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© Copyright 2013 The University of Edinburgh - 16 April 2013 4:36 am