Mathematical Statistical Mechanics (MAST90060)
Graduate courseworkPoints: 12.5On Campus (Parkville)
Overview
| Availability | Semester 1 |
|---|---|
| Fees | Look up fees |
The goal of statistical mechanics is to describe the behaviour of bulk matter starting from a physical description of the interactions between its microscopic constituents. This subject introduces the Gibbs probability distributions of classical and quantum statistical mechanics, the relations to thermodynamics and the modern theory of phase transitions and critical phenomena. The central concepts of critical exponents, universality and scaling are emphasized throughout. Applications include the ideal gases, magnets, fluids, one-dimensional Ising and Potts lattice spin models, random walks and percolation as well as approximate methods of solution.
Intended learning outcomes
After completing this subject students should be able to:
- Describe how the ensembles and methods of classical and quantum statistical mechanics apply to a variety of problems in applied mathematics and mathematical physics;
- Explain the role of critical phenomena in modern thermodynamics and use the principles of critical exponents, universality and scaling to examine the behaviour of complex systems;
- Describe the basic concepts of phase transitions as applied to fluids, magnets, lattice spin models, random walks and percolation and use them to analyse such systems; and
- Use the basic mathematical techniques of statistical mechanics including transfer matrices, real-space renormalization group and approximate methods to analyse a variety of systems.
Generic skills
In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:
- Problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
- Analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
- Collaborative skills: the ability to work in a team; and
- Time-management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 11 March 2025
Eligibility and requirements
Prerequisites
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST20009 | Vector Calculus |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
| MAST20032 | Vector Calculus: Advanced | Semester 1 (On Campus - Parkville) |
12.5 |
Corequisites
Non-allowed subjects
No disallowed subject combinations among new-generation subjects.
Recommended background knowledge
It is recommended that students have completed the following, or equivalent.
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST20026 | Real Analysis |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
No prior knowledge of physics or thermodynamics is assumed.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 11 March 2025
Assessment
| Description | Timing | Percentage |
|---|---|---|
Written assignment up to 10 pages
| From Week 3 to Week 6 | 10% |
Written assignment up to 15 pages
| From Week 6 to Week 9 | 15% |
Written assignment up to 15 pages
| From Week 9 to Week 12 | 15% |
A written examination
| During the examination period | 60% |
Last updated: 11 March 2025
Dates & times
- Semester 1
Coordinator Thomas Quella Mode of delivery On Campus (Parkville) Contact hours 36 hours comprising of 3 one-hour interactive lectures per week. Total time commitment 170 hours Teaching period 3 March 2025 to 1 June 2025 Last self-enrol date 14 March 2025 Census date 31 March 2025 Last date to withdraw without fail 9 May 2025 Assessment period ends 27 June 2025 Semester 1 contact information
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 11 March 2025
Further information
- Texts
- Related Handbook entries
This subject contributes to the following:
Type Name Course Ph.D.- Engineering Course Master of Science (Mathematics and Statistics) Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Informal specialisation Mathematics and Statistics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Last updated: 11 March 2025