PURE MTH 7002 - Pure Mathematics Topic B
North Terrace Campus - Semester 1 - 2018
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General Course Information
Course Details
Course Code PURE MTH 7002 Course Pure Mathematics Topic B Coordinating Unit Mathematical Sciences Term Semester 1 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: Dr Hang Wang
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 2018, the topic of this course is Functional Analysis
Introduction
Motivated by the development of calculus of variation, integral equations, approximation theory and quantum physics in early years of the twenties century, functional analysis has grown into a broad field of modern analysis. This subject is the study of infinite dimensional linear topological spaces as well as properties of linear maps among these spaces, using analysis, algebra and geometry. Just as finite dimensional vector space is the representation space to linear algebra, Hilbert space is the natural representation space to functional analysis. Analysis and spectral theory of linear operators on Hilbert spaces are essential tools in mathematics, physics, and many branches in engineering sciences, especially in fields of Partial Differential Equation, Quantum Mechanics, Signal Processing, Ergodic Theory and Dynamics.
This course focuses on important examples, properties, and linear operators on Hilbert spaces, and leads to spectral theorem of Hermite operators. Time permitted, we shall explore some advanced topics of the field. This course is fundamental to students planning to study and research in modern mathematics and/or physics.
The course will cover the following topics.
1. Hilbert spaces (4 lectures).
2. Bounded linear operators on Hilbert spaces and fundamental theorems in functional analysis (8 lectures).
3. Special operators (6 lectures).
4. Compact operators and its spectral decompositions (4 lectures).
5. Spectral decomposition of Hermite operators (6 lectures).
6. Advanced topics (sample: unbounded operators, representation of groups, Fourier analysis) (2 lectures).
Learning Outcomes
On successful completion of this course, students will be able to
1. Understand properties of Hilbert spaces and their bounded linear operators; know how to apply these properties;
2. Identify and work on key examples involving Hilbert space analysis;
3. Understand meaning of spectrum and compute spectrum of specific examples;
4. State and prove spectral theorem for compact and for Hermite operators;
5. Know some concrete applications of spectral theorem.
Prerequisites
The course requires point set topology, basic measure theory, firm background in linear algebra. Good knowledge of complex analysis and real analysis would be desirable. It is recommended that students have taken Topology and analysis III previously and are familiar with basics ideas of linear algebra and groups.最新糖心Vlog Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
最新糖心Vlog Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
all Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
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Learning Resources
Required Resources
The only required resources for this course is my lecture notes.Recommended Resources
W. Rudin, Functional analysis
J. Convey, A course in functional analysis
M. Reed and B. Simon, Methods of modern mathematical physics. I, Functional analysis; II, Fourier analysis, self-adjointness
K. Yosida, Functional analysis
G. Folland, Real analysis: Modern techniques and their applicationsOnline Learning
The course will have an active MyUni website. -
Learning & Teaching Activities
Learning & Teaching Modes
The lecturer guides the students through the course material in 30 lectures. Students are expected to engage with the material in the lectures. Interaction with the lecturer and discussion of any difficulties that arise during the lecture is encouraged. Fortnightly homework assignments help students strengthen their understanding of the theory and their skills in applying it, and allow them to gauge their progress.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 90 Assignments 6 66 Total 156 Learning Activities Summary
No information currently available.
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Assessment
The 最新糖心Vlog'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
Assessment task Task type Due Weighting Learning outcomes Examination Summative Examination period 70% All Homework assignments Formative and summative One week after assigned 30% All Assessment Related Requirements
An aggregate score of 50% is required to pass the course.Assessment Detail
There will be a total of 6 homework assignments, distributed during every 4 lectures and due within 1 week. Each will cover material from the lectures and, in addition, will sometimes go beyond that so that students may have to undertake some additional research.Submission
Homework assignments must be given to the lecturer in person or emailed as a pdf. Failure to meet the deadline without reasonable and verifiable excuse may result in a significant penalty for that assignment.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 最新糖心Vlog 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 最新糖心Vlog 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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Fraud Awareness
Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.
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