MXN424 Advanced Applied Analysis
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | MXN424 |
|---|---|
| Other requisite(s): | Unit Coordinator approval required |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $592 |
| Domestic tuition unit fee | $3,900 |
| International unit fee | $5,220 |
Unit Outline: Semester 2 2026, Gardens Point, Internal
| Unit code: | MXN424 |
|---|---|
| Credit points: | 12 |
| Other Requisite: | Unit Coordinator approval required |
| Coordinator: | Matthew Simpson | matthew.simpson@qut.edu.au |
Overview
This unit provides a framework for you to undertake advanced level coursework in applied analysis. It will provide you with a sound understanding and appreciation of a range of advanced theories, concepts and techniques selected from areas such as asymptotic analysis, perturbation theory, functional analysis, complex analysis, graph theory and algebraic geometry. You will gain expertise in problem formulation, problem solving, critical thinking and written communication. This advanced unit builds upon the analysis work previously undertaken in an undergraduate mathematics degree, such as differential equations and linear algebra. It is also designed to complement a research project in applied and/or computational mathematics and prepare you for further research studies at Masters or PhD level.
Learning Outcomes
On successful completion of this unit you will be able to:
- Formulate problems in mathematical terms and perform related advanced level analysis.
- Apply problem-solving skills in the types of extended problems that arise in the highly quantitative area of applied analysis.
- Employ high level mathematical manipulation, algebraic and conceptual skills.
- Articulate and communicate ideas using high-level mathematical notation and language.
Content
The unit is designed to provide you with knowledge, skills and application in a number of techniques that fall into the broad area of applied analysis.
A selection of the following (or related) topics will be covered:
1. Linearisation and perturbation expansions of differential equations
2. Asymptotic approximations, matched asymptotics
3. Functional and complex analysis
4. Graph-theoretic methods for analysis of polynomial dynamical systems
5. Algebraic geometry methods for computation of polynomial invariants
Learning Approaches
This unit involves a combination of lectures and reading material where theory and concepts will be presented, and where you will be exposed to the processes required to solve problems using the methods of this unit.
The teaching and learning approaches will foster both acquisition of new knowledge at an advanced level and development of your skills. The material presented will be context-based utilising examples from a range of mathematical and real-world applications. The emphasis will be on learning by doing, learning in groups and as individuals, written and oral communication, and developing skills and attitudes to promote life-long learning.
You are expected to work not only in any lecture/workshop session times allocated, but also in your own private study time. That is, you are expected to consolidate the material presented by working through a wide variety of exercises, problems and online learning activities in your own time.
Feedback on Learning and Assessment
Feedback will be provided by academic staff through summative assessment tasks and through formative feedback during timetabled classes. You will also have opportunities for peer-to-peer learning and self-reflection to support your learning and skills development.
Assessment
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Case Study
You will be required to solve a series of mathematical problems to demonstrate the range of analytical techniques learned in this unit and communicate your solutions in a format appropriate to the academic and professional practice of the mathematical sciences. These mathematical problems may be of an unfamiliar form or nature and will be taken from, and simulate, authentic real-world research questions in the field of applied mathematics.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
The use of Generative AI tools is prohibited for this assessment. Please see the Assessment page on the canvas site for the unit for any further explanation.
Assessment: Examination
You will be required to complete a series of written mathematical exercises that test your understanding of the material covered over the semester.
The use of Generative AI tools is prohibited for this assessment. Please see the Assessment page on the canvas site for the unit for any further explanation.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
Risk Assessment Statement
There are no extraordinary risks associated with the classroom/lecture activities in this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.MS10 Bachelor of Mathematics (Honours)
- Demonstrate and apply advanced knowledge and skills in mathematical sciences to critically analyse and solve complex problems within the discipline or in cross-disciplinary fields where mathematics underpins innovation
Relates to: Case Study, Examination - Communicate complex concepts, methods and findings in the mathematical sciences clearly and effectively to a range of audiences including mathematicians, industry professionals and the general public, using a range of academic, professional, and technical formats
Relates to: Case Study, Examination