NONLINEAR PATTERNS - 2017/8
Module code: MATM031
LLOYD D Dr (Maths)
Number of Credits
FHEQ Level 7
Module cap (Maximum number of students)
Overall student workload
|Assessment type||Unit of assessment||Weighting|
|School-timetabled exam/test||IN-SEMESTER TEST||20|
Prerequisites / Co-requisites
N/A Qualifying Condition(s) A weighted aggregate mark of 50% is required to pass the module
Regular patterns arise naturally in many physical and biological systems, from hexagonal convection cells on the surface of the sun to stripes on a zebra's back. This course provides a basic framework for understanding the formation and evolution of these patterns using ordinary and partial differential equations and group theory.
To become familiar with a range of symmetry-based techniques for describing the behaviour of regular patterns that occur in nature or in laboratory experiments.
|Be able to locate and classify codimension-one bifurcations of ordinary differential equations||KC|
|Be familiar with the concept of a centre manifold||K|
|Be able to identify the symmetry group relevant to simple pattern formation problems and use the Equivariant Branching Lemma in simple cases||KC|
|Understand how to describe patterns using amplitude equations, and be able to find solutions of these equations in simple cases||KC|
|Understand how to describe spatially modulated patterns using envelope equations, and be able to find solutions of these equations in simple cases||KC|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Indicative content includes:
a review of flows and stationary points of ordinary differential equations, moving on to the concepts of centre manifolds and bifurcations. Simple bifurcations will be described and classified.
group theoretic methods for analysing pattern-forming systems. Patterns on lattices and in boxes will be studied using symmetry groups. The Equivariant Branching Lemma and representations of groups will be covered.
The module will conclude with the description of spatially-modulated patterns in terms of envelope equations. The Ginzburg-Landau equation will be derived and used to study the properties of stripes.
Methods of Teaching / Learning
The learning and teaching strategy is designed to provide:
- A detailed introduction to nonlinear patterns and their analysis
- Experience (through demonstration) of the methods used to analyse, understand and solve problems involving nonlinear patterns.
The learning and teaching methods include:
3 x 1 hour lectures per week x 11 weeks, with projector-displayed written notes to supplement the module handbook and Q + A opportunities for students.
The assessment strategy is designed to provide students with the opportunity to demonstrate
Subject knowledge through the recall of key definitions, theorems and methods.
Analytical ability through the solution of unseen problems in the test and exam.
Thus, the summative assessment for this module consists of:
One two hour examination (two of three best answers contribute to exam mark, with Question 1 compulsory) at the end of Semester 1; worth 75% module mark.
One 50 minute in-semester test; worth 25% module mark.
Formative assessment and feedback
Students receive written feedback via two marked coursework assignments over an 11 week period. In addition, verbal feedback is provided by lecturer/class tutor at biweekly seminars and weekly tutorial lectures.
Reading list for NONLINEAR PATTERNS : http://aspire.surrey.ac.uk/modules/matm031
Programmes this module appears in
|Mathematics 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 and Physics MMath/MPhys||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 2017/8 academic year.