CALCULUS OF VARIATIONS - 2022/3
Module code: MATM059
Module Overview
The objective of this module is to introduce students to some of the classical and modern methods in the Calculus of Variations. There will be many examples to illustrate the theory in action.
Module provider
Mathematics & Physics
Module Leader
BEVAN Jonathan (Maths & Phys)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
Module cap (Maximum number of students): 30
Overall student workload
Independent Learning Hours: 79
Lecture Hours: 33
Seminar Hours: 5
Captured Content: 33
Module Availability
Semester 2
Prerequisites / Co-requisites
MAT1032 Real Analysis 1 and MAT2004 Real Analysis 2, or equivalent.
Module content
• Variational symmetries and conservation laws.
• Weak derivatives, the fundamental lemma of the Calculus of Variations, and the spaces Lp(a,b) and W1,p(a,b).
• The weak Euler-Lagrange equation.
• Convexity and the Legendre condition.
• Solving the Euler-Lagrange equation. Examples to include the brachistochrone, minimal surfaces of revolution, the catenary.
• The direct method of the Calculus of Variations. Examples of problems with no minimizer.
• Weak and strong local minimizers: sufficient conditions for a solution of the Euler-Lagrange equation to be a minimizer.
• Constrained variational problems.
Assessment pattern
| Assessment type | Unit of assessment | Weighting |
|---|---|---|
| School-timetabled exam/test | In-semester test (50 mins) | 20 |
| Examination | Exam (2 hrs) | 80 |
Alternative Assessment
N/A
Assessment Strategy
The strategy of assessment via Examination and In-Semester Test is designed to provide:
• A detailed introduction to the classical and modern methods in the Calculus of Variations
• Experience of the methods used to interpret, understand and solve applicable problems using such techniques.
Module aims
- Equip students with some of the basic tools of the Calculus of Variations
- Develop the students’ appreciation of where the Calculus of Variations is useful and how it fits in with other mathematical disciplines
Learning outcomes
| Attributes Developed | ||
| 001 | Accurately identify conditions under which the Euler-Lagrange equation can be derived, and to derive it from first principles under these conditions | KCT |
| 002 | Recognize and determine appropriate function spaces in which to set given variational problems, and to apply previous knowledge of ordinary differential equations in order to solve them | KC |
| 003 | Understand and apply theorems concerning weak and strong local minimizers to given variational problems | KC |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching methods include:
• 3 x 1 hour lectures per week x 11 weeks interspersed with tutorials when appropriate for 11 weeks.
• Formative feedback will be provided both on submitted problem sheets and in the In-Semester test, to help students develop their understanding as the course progresses.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Reading list
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: MATM059
Other information
This module has a capped number and may not be available to ERASMUS and other international exchange students. Please check with the International Engagement Office email: ieo.incoming@surrey.ac.uk
Programmes this module appears in
| Programme | Semester | Classification | Qualifying conditions |
|---|---|---|---|
| Mathematics with Statistics MMath | 2 | Optional | A weighted aggregate mark of 50% is required to pass the module |
| Mathematics MSc | 2 | Optional | A weighted aggregate mark of 50% is required to pass the module |
| Mathematics MMath | 2 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.