FUNCTIONAL ANALYSIS AND PARTIAL DIFFERENTIAL EQUATIONS - 2017/8

Module code: MATM022

Module provider

Mathematics

ZELIK S Prof (Maths)

Number of Credits

15

ECTS Credits

7.5

Framework

FHEQ Level 7

JACs code

G100

Module cap (Maximum number of students)

N/A

Module Availability

Semester 1

Independent Study Hours: 117

Lecture Hours: 33

Assessment pattern

Assessment type Unit of assessment Weighting
Examination 2 HOUR EXAMINATION 75
School-timetabled exam/test IN-SEMESTER TEST 1 (50 MINS) 13
School-timetabled exam/test IN-SEMESTER TEST 2 (50 MINS) 12

Alternative Assessment

N/A

Prerequisites / Co-requisites

MAT2004, MAT2011

Module overview

This module introduces the basic concepts of functional analysis including Hilbert and Banach spaces, the associated spaces of linear functionals, weak convergences, etc. The introduced concepts are then used to give an introduction to the modern theory of partial differential equations.

Module aims

The aim of this module is to introduce students to basic concepts and methods of functional analysis with applications to PDEs.

Learning outcomes

Attributes Developed
1 Have an understanding of basic properties of Hilbert and Banach spaces and associated linear operators; K
2  Understand a concept of a distributional solution of a differential equation and to be able to give a weak formulation for the Dirichlet and Neumann problems for the Laplace operator; KC
3 Be able to prove the existence and uniqueness of a solution for some classical partial differential equations using the methods of functional analysis. KCT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Module content

Indicative content includes:

Hilbert and Banach spaces, linear functionals, dual spaces, reflexivity.
Weak and strong convergences. Weak compactness of a unit ball in reflexive spaces.
Introduction to distributions and Sobolev spaces.
Weak formulation of Dirichlet and Neumann problems for the Laplacian.
Variational formulation of these problems.
Introduction to non-linear partial differential equations.

Methods of Teaching / Learning

The learning and teaching strategy is designed to provide:

A detailed introduction to basic concepts and methods of functional analysis with applications to PDEs.
Experience (through demonstration) of the methods used to interpret, understand and solve/prove problems in functional analysis and PDEs.

The learning and teaching methods include:

3 x 1 hour lectures per week x 11 weeks, with blackboard/whiteboard notes to supplement the module lecture notes and Q + A opportunities for students.

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate:

·         Understanding of and ability to solve/prove problems in operator and PDE theories.

·         Subject knowledge through the recall of key definitions, theorems and their proofs.

·         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 (three of four best answers contribute to exam mark) at the end of Semester 1; worth 75% module mark.

·         Two in-semester tests; each worth 12.5% module marks.

Formative assessment and feedback

Students receive written feedback via a number of marked coursework assignments over an 11 week period.  In addition, verbal feedback is provided by lecturer at tutorials.