This course is an introduction to quantum computing, covering theory and practice (through the use of simulation software). The main topics are: quantum information processing; quantum protocols for communication (teleportation, dense coding, error correction) and cryptography (key distribution); quantum algorithms (Deutsch's algorithm, Grover's algorithm, overview of Shor's algorithm); quantum annealing

2 hours of lecture time and 1 hour of tutorial or practical work, per week

None

None

80% for the end-of-year exam

20% for assessed coursework, which is likely to be separated into two smaller assignments

The assessed coursework will assess ILOs 5 and 7

The exam will assess ILOs 1, 2, 3, 4 and 6

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

The aim of the course is to introduce the theory and practice of quantum computing.

By the end of this course students will be able to:

1. Explain the principles of quantum computation and the characteristics that distinguish it from classical computation.

2. Calculate the effect of quantum protocols and algorithms according to the laws of Hilbert spaces.

3. Use the notation of quantum circuit diagrams to define and understand quantum protocols and algorithms.

4. Understand specific quantum algorithms and protocols and be able to evaluate them on example data: Deutsch's algorithm, Grover's algorithm, quantum teleportation, quantum dense coding, the BB84 key distribution protocol, at least one error-correction protocol.

5. Express and work with quantum algorithms and protocols in a standard simulation environment, e.g. Qiskit

6. Explain the principles of quantum annealing and its key differences from algorithmic quantum computing.

Use a standard quantum annealing framework (e.g. D-Wave) to model and solve standard optimisation problems.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.