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COMP SCI 4813 - Introduction to Quantum Computing

North Terrace Campus - Semester 1 - 2020

It is still unknown whether quantum computers will ever be a reality. If such machines are possible, they will fundamentally change how we perform calculations, and the implications on many applications (including communications and computer security) will be tremendous. Leaving the issue of feasibility aside, it is interesting nonetheless to study how to do computing using a quantum computer. This course aims to provide a first introduction to quantum computing. We will highlight the paradigm change between conventional computing and quantum computing, and introduce several basic quantum algorithms. If time permits, we will also discuss the implications of quantum computing on fields such as computer security and machine learning.

  • General Course Information
    Course Details
    Course Code COMP SCI 4813
    Course Introduction to Quantum Computing
    Coordinating Unit Computer Science
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites COMP SCI 2201
    Assumed Knowledge MATHS 1004 or MATHS 1012; COMP SCI 2103
    Assessment Written exam and / or assignments
    Course Staff

    Course Coordinator: Professor Tat-Jun Chin

    Course Timetable

    The full timetable of all activities for this course can be accessed from .

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion, students will gain understanding of:
    1. The basic principles of quantum computing.
    2. The fundamental differences between conventional computing and quantum computing.
    3. Several basic quantum computing algorithms.
    4. The classes of problems that can be expected to be solved well by quantum computers.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University 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)
    1,2,3,4
    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
    1,2,3,4
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    1,2,3,4
  • Learning Resources
    Required Resources
    Students must be enrolled in the course on MyUni to obtain course material and receive important announcments.
    Recommended Resources
    The main textbook used in the course is Quantum Computing: A Gentle Introduction, by Eleanor Rieffel and Wolfgang Polak (available from the university library), and Quantum Computing for Computer Scientists, by Noson Yanofsky and Mirco Mannucci.
  • Learning & Teaching Activities
    Learning & Teaching Modes

    No information currently available.

    Workload

    No information currently available.

    Learning Activities Summary

    No information currently available.

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    • 4 assignments at 10% weighting each.
    • Final exam at 60% weighting.

    Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.

    In place of a written final exam for the course, we will be conducting an online exam (likely to be open book).

    The current plan is for the online exam to occur either at the exact same date and time scheduled for the original physical exam
    (to be released by the exams office later); or at another suitable date and time in the exams period (if the exams
    office will not be releasing an exams schedule this semester).

    In either case, please make yourself available in the exams period to take the exam.

    The current plan is to conduct the online exam via MyUni (though this is subject to the system being properly tested and verified for this purpose), so you need to make sure that you have a good Internet connection to not be disadvantaged during the exam.

    Note that the online exam is the only option - we will not be holding a physical exam simultaneously.

    All other course work (Assignments 1-4) will proceed as per normal with online submissions.
    Assessment Detail

    No information currently available.

    Submission
    Submit on MyUni.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M11 (Honours Mark Scheme)
    GradeGrade reflects following criteria for allocation of gradeReported on Official Transcript
    Fail A mark between 1-49 F
    Third Class A mark between 50-59 3
    Second Class Div B A mark between 60-69 2B
    Second Class Div A A mark between 70-79 2A
    First Class A mark between 80-100 1
    Result Pending An interim result RP
    Continuing Continuing CN

    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 .

  • Student Feedback

    The University 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 University 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.

  • Student Support
  • Policies & Guidelines
  • 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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