PURE MTH 7023 - Pure Mathematics Topic D
North Terrace Campus - Semester 2 - 2016
The course information on this page is being finalised for 2016. Please check again before classes commence.
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General Course Information
Course Details
Course Code PURE MTH 7023 Course Pure Mathematics Topic D Coordinating Unit Mathematical Sciences Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Available for Study Abroad and Exchange Y Assessment ongoing assessment 30%, exam 70% Course Staff
Course Coordinator: Professor Mathai Varghese
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
In 2014, the topic of this course will be Functional Analysis.
Syllabus
Motivated by the development of the calculus of variations, integral equations, approximation theory and quantum physics in the early years of the 20th century, functional analysis has grown into a broad field of modern analysis. It studies infinite-dimensional linear topological spaces, in particular Hilbert spaces, and properties of maps between such spaces, using analysis, algebra and geometry. The course focuses on important examples and properties of Hilbert spaces and operators on Hilbert spaces, leading to the spectral theorem for Hermitian operators. Time permitting, we will explore some applications in group representation theory, Fourier analysis and other advanced topics. The course provides a foundation for further studies in both mathematics and physics.
The topics to be covered includes a review of Hilbert spaces; bounded linear operators on Hilbert spaces and fundamental theorems in functional analysis; compact operators and other examples of operators; Gelfand transform and spectral decomposition; application to group representations, application to Fourier analysis.
The prerequisites for the course are Topology and Analysis III, and Integration and Analysis III. A good background in linear algebra and real and complex analysis is desirable, as well as some familiarity with groups and manifolds.
Learning Outcomes
Students completed the course will be able to:
1. fully comprehend the statement of fundamental theorems of functional analysis and the concepts relating to them;
2. demonstrate knowledge of the tools of the theory of Hilbert spaces;
3. be able to solve functional analysis problems using modern analysis;
4. recognise a problem in other areas of mathematics that can be solved using functional analysis;
5. demonstrate an understanding of the spectral theorem in functional analysis and its role in other relavent subjects in pure mathematics and physics.
6. demonstrate basic understanding and skill in group representation theory and fourier analysis.
7. demonstate skill in communicating mathematics orally and in writing.University Graduate Attributes
No information currently available.
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Learning Resources
Required Resources
None.Recommended Resources
- J.B. Conway: A Course in Functional Analysis.
- W. Rudin: Functional Analysis.
- V.S. Sunder: Functional Analysis: Spectral Theory.
- M. Reed and B. Simon, Methods of Modern Mathematical Physics, Volume 1, Functional Analysis.
- G. Folland: A Course in Abstract Harmonic Analysis.
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Learning & Teaching Activities
Learning & Teaching Modes
The course consists of 30 lectures and 6 assignments. The students are expected to participate actively in the lectures and complete the assignments on time (the assignments will be collected every two weeks). Upon students' need there will be extra tutorials to solve problems and to learn more details or topics beyond the lectures.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Quantity Workload Hours Lectures 30 114 Assignments 6 42 Total 156 Learning Activities Summary
- Review of Hilbert space (2 lectures).
- Bounded linear operators on Hilbert space (4 lectures).
- Fundamental theorems of functional analysis (5 lectures).
- Compact operators and other types of operators (4 lectures).
- Spectral theorem (6 lectures).
- Applications to group representation theory (4 lectures).
- Applications to Fourier analysis (5 lectures).
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Assessment
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
Component Weighting Learning Outcomes Assignments 30% all Test 70% all Assessment Related Requirements
An aggregate score of at least 50% is required to pass the course.Assessment Detail
Distributed Due Date Weighting Assignment 1 Week 1 Week 2 5% Assignment 2 Week 3 Week 4 5% Assignment 3 Week 5 Week 6 5% Assignment 4 Week 7 Week 8 5% Assignment 5 Week 9 Week 10 5% Assignment 6 Week 11 Week 12 5% Submission
Assignments will be collected at the beginning of a lecture, every two weeks. Late assignments will not be accepted.Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through .
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Student Feedback
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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