Experimental Mathematics

Subject MAST90053 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 29-Feb-2016 to 29-May-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 11-Mar-2016
Census Date 31-Mar-2016
Last date to Withdraw without fail 06-May-2016

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours: One 1-hour lecture per week and one 2-hour practical class per week
Total Time Commitment:

170 hours


One of the following, or equivalent.

Study Period Commencement:
Credit Points:
Semester 1


Recommended Background Knowledge:

It is recommended that students have completed the following, or a similar subject.

Study Period Commencement:
Credit Points:
Non Allowed Subjects:


Core Participation Requirements:

Students will be expected to carry out computational experiments using symbolic packages.

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/


Prof Jan De Gier


Email: jdgier@unimelb.edu.au

Subject Overview:

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.

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.

Up to 40 pages of written assignments (30%: two assignments worth 15% each, due mid and late in semester), a take home exam (70%, in the examination period).

Prescribed Texts:


Recommended Texts:

M. Petkovsek, H. Wilf and D. Zeilberger, A=B

Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
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.
Related Course(s): Doctor of Philosophy - Engineering
Master of Philosophy - Engineering
Master of Science (Mathematics and Statistics)
Related Majors/Minors/Specialisations: Mathematics and Statistics

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