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Experimental Mathematics (MAST90053)
Graduate courseworkPoints: 12.5Not available in 2024
Overview
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Modern computers have developed far beyond being great devices for numerical simulations or tedious but straightforward algebra; and in 1990 the first mathematical research paper was published whose sole author was a thinking machine known as Shalosh B Ekhad. This course will discuss some of the great advances made in using computers to purely algorithmically discover (and prove!) nontrivial mathematical theorems in for example Number Theory and Algebraic Combinatorics. Topics include: Automated hypergeometric summation, Groebner basis, Chaos theory, Number guessing, Recurrence relations, BBP formulas.
Intended learning outcomes
After completing this subject, students will:
- have been introduced to non-numerical symbolic computation packages used in modern research in the areas of discrete mathematics and number theory;
- acquire insight into the use of computers for discovering and formally proving mathematical theorems;
- gain the ability to pursue further studies in this and related areas.
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;
- time-management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 30 January 2024
Eligibility and requirements
Prerequisites
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST30005 | Algebra | Semester 1 (On Campus - Parkville) |
12.5 |
| MAST30012 | Discrete Mathematics | Semester 2 (On Campus - Parkville) |
12.5 |
| MAST30028 | Numerical Methods & Scientific Computing | Semester 2 (On Campus - Parkville) |
12.5 |
Or equivalent
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
It is recommended that students have completed the following, or a similar subject.
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST30028 | Numerical Methods & Scientific Computing | Semester 2 (On Campus - Parkville) |
12.5 |
Inherent requirements (core participation requirements)
Students will be expected to carry out computational experiments using symbolic packages.
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: 30 January 2024
Assessment
| Description | Timing | Percentage |
|---|---|---|
Up to 40 pages of written assignments (two assignments worth 15% each, due mid and late in semester)
| Second half of the teaching period | 30% |
A take home exam | During the examination period | 70% |
Last updated: 30 January 2024
Dates & times
Not available in 2024
Time commitment details
170 hours
Last updated: 30 January 2024
Further information
- Texts
Prescribed texts
None
Recommended texts and other resources
M. Petkovsek, H. Wilf and D. Zeilberger, A=B
- Related Handbook entries
This subject contributes to the following:
Type Name Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Course Master of Philosophy - Engineering Course Master of Science (Mathematics and Statistics) 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.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 30 January 2024