# DEGREE REGULATIONS & PROGRAMMES OF STUDY 2018/2019

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DRPS : Course Catalogue : School of Mathematics : Mathematics

# Undergraduate Course: Numerical Ordinary Differential Equations and Applications (MATH10060)

 School School of Mathematics 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 Most ordinary differential equations (ODEs) lack solutions that can be given in explicit analytical formulas. Numerical methods for ODEs allow for the computation of approximate solutions and are essential for their quantitative study. In some cases, a numerical method can facilitate qualitative analysis as well, such as probing the long term solution behaviour. As well as studying the theory, the course has a strong emphasis on implementation of these methods (in Matlab) to tackle modern applications of ODEs. Course description This course begins by introducing basic numerical schemes, such as Euler's method, including a study of their derivation and convergence properties. It then discusses more accurate approaches such as Taylor series methods, numerical quadrature, and Runge-Kutta schemes, in terms of both their theoretical properties and practical implementation. The related ideas of consistency, stability and convergence of numerical methods will then be studied, as well as the corresponding order conditions for Runge-Kutta schemes. Motivated by a range of applications, more advanced techniques such as variable step size methods and linear multi-step approaches will be developed, again studying both theoretical and practical aspects. Finally, more specialised schemes will be presented. These are strongly application-dependent and could include geometric integration, symplectic methods, splitting schemes, shooting methods, or techniques for tackling differential-algebraic equations. There is a strong focus on modern applications and numerical implementation throughout the course, which will serve to enhance existing programming skills and broaden knowledge of modern areas of applied mathematics.
 Pre-requisites Students MUST have passed: ( Honours Differential Equations (MATH10066) OR Dynamics and Vector Calculus (PHYS08043)) AND ( Computing and Numerics (MATH08065) OR Computer Simulation (PHYS08026) OR Programming and Data Analysis (PHYS08049)) Co-requisites Prohibited Combinations Other requirements None
 Pre-requisites None High Demand Course? Yes
 Academic year 2018/19, Available to all students (SV1) Quota:  None Course Start Semester 2 Timetable Timetable Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 10, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 64 ) Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 % Additional Information (Assessment) Coursework 50%, Examination 50% Feedback Not entered Exam Information Exam Diet Paper Name Hours & Minutes Main Exam Diet S2 (April/May) Numerical Ordinary Differential Equations and Applications (MATH10060) 2:00
 On completion of this course, the student will be able to: determine appropriate numerical methods to solve a range of ODEs.implement such numerical methods in a suitable programming language.derive and analyse such methods and their errors.understand the principles of consistency, stability and convergence.apply the above to examples from modern applied mathematics.
 An electronic set of lecture notes will be provided. Students may find the following useful: D. Griffiths and D. Higham, Numerical Methods for Ordinary Differential Equations, Springer 2010 A. Iserlies, A First Course in the Numerical Analysis of Differential Equations, Cambridge University Press, 2008 L. N. Trefethen, Finite Difference and Spectral Methods for Ordinary and Partial Differential Equations
 Graduate Attributes and Skills Not entered Keywords NuODE
 Course organiser Dr Benjamin Goddard Tel: (0131 6)50 5127 Email: B.Goddard@ed.ac.uk Course secretary Miss Sarah McDonald Tel: (0131 6)50 5043 Email: sarah.a.mcdonald@ed.ac.uk
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