43025 Introduction to Quantum Computing
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Subject handbook information prior to 2025 is available in the Archives.
Credit points: 6 cp
Result type: Grade and marks
Requisite(s): 37151 Introduction to Statistics OR 33230 Mathematics 2 OR 33290 Statistics and Mathematics for Science
These requisites may not apply to students in certain courses. See access conditions.
Recommended studies:
Basic linear algebra, calculus, and discrete mathematics
Description
This subject introduces quantum computation, a model of computation based on the physical laws of quantum mechanics. Quantum computers outperform traditional computers for a range of practical problems, and in many cases offer drastic advantages.
In this subject, students learn about the basic tools for understanding quantum information processing. This knowledge is applied to study the key quantum protocols: teleportation, superdense coding, and simple quantum algorithms.
The subject covers key features of quantum theory which differentiate it from classical theory, including quantum entanglement and coherence.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Analyse quantum information protocols using the basic mathematical structure of quantum mechanics, including states, operations and measurements to validate performance claims. (D.1) |
|---|---|
| 2. | Design and create quantum circuits for quantum algorithms to run on quantum computers. (D.1) |
| 3. | Critically reflect and contrast the historical development of quantum and classical computation to differentiate computational capabilities. (D.1) |
| 4. | Effectively communicate quantum concepts to broad audiences. (E.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Technically Proficient: FEIT graduates apply theoretical, conceptual, software and physical tools and advanced discipline knowledge to research, evaluate and predict future performance of systems characterised by complexity. (D.1)
- Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating autonomously within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)
Teaching and learning strategies
This subject consists of a combination of complementary in-class and self-study activities. Before class meetings, students will be expected to engage with background material that will adapt the fundamental concepts of statistics to quantum computing contexts. The face-to-face classes (one lecture, tutorial, and computer laboratory per week) will incorporate a range of teaching and learning strategies including the presentation of worked examples, critiquing readings, collaborative group work and individual problem solving. Students are to review the relevant material made available on Canvas prior to classes, and complete any associated tasks, before attending the corresponding session. Students will use specialist statistical software extensively in the laboratory classes to analyse real quantum circuits, both in groups and individually. Online Exercises are provided for which feedback on student attempts is given immediately.
Content (topics)
- Quantum states and their properties: coherence, entanglement
- Quantum processes: single and two qubit gates
- Quantum measurements: structure and statistical properties
- Quantum circuits
- Quantum protocols: teleportation, superdense coding, Deutsch’s algorithm
Assessment
Assessment task 1: Weekly quizzes
| Intent: | For students to benchmark their understanding of concepts presented within the weekly subject sessions |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1 and 2 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 |
| Type: | Quiz/test |
| Groupwork: | Individual |
| Weight: | 40% |
| Length: | Varying between 10 and 20 questions. |
Assessment task 2: In-Lab critiquing
| Intent: | This assessment task contributes to the development of quantum computing knowledge and its appropriate application, as well as contextualising professional and communication skills within the quantum computing discipline. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Exercises |
| Groupwork: | Group, individually assessed |
| Weight: | 30% |
| Length: | 5 minute presentations within each designated lab session. |
Assessment task 3: In-Lab presentations
| Intent: | This assessment task contributes to the development of quantum computing knowledge and its appropriate application, as well as contextualising professional and communication skills within the quantum computing discipline. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 and E.1 |
| Type: | Presentation |
| Groupwork: | Group, individually assessed |
| Weight: | 30% |
| Length: | 5 minute presentations within each designated lab session. |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more.
Required texts
Quantum Computation and Quantum Information: 10th Anniversary Edition, by Michael Nielsen and Isaac Chuang.
Recommended texts
Quantum Computing for Highschool Students
Quantum Computing for Everyone?
Other resources:
IBMQ?