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This is an archived syllabus from 2020-2021

COMP39112 Quantum Computing syllabus 2020-2021

COMP39112 Quantum Computing

Level 3
Credits: 10
Enrolled students: 105

Course leader: Richard Banach

Additional staff: view all staff

Additional requirements

  • Pre-requisites

    You have to be happy to do plenty of mathematics, linear algebra in particular. The material is covered in the course itself (and includes topics in linear algebra not covered elsewhere), but it's a great help if you've seen (at least some) linear algebra before. By all means contact me if you're unsure.

Assessment methods

  • 100% Written exam
Sem 2 INDEPENDENT STUDY Fri 09:00 - 10:00 -
Sem 2 INDEPENDENT STUDY Wed 11:00 - 12:00 -
Sem 2 ONLINE ACTIVITY Wed 17:00 - 18:00 -
Sem 2 w30,32 ONLINE Lecture Simon TH E Wed 17:00 - 18:00 -


Quantum computing is one of the most intriguing of modern developments at the interface of computing, mathematics and physics, whose long term impact is far from clear as yet.

This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.


The perspective that quantum phenomena bring to the questions of information and algorithm is quite unlike the conventional one. In particular, selected problems which classically have only slow algorithms, have in the quantum domain, algorithms which are exponentially faster. Most important among these is the factoring of large numbers, whose difficulty underpins the security of the RSA encryption protocol, used for example in the secure socket layer of the internet. If serious quantum computers could ever be built, RSA would become instantly insecure. This course aims to give the student an introduction to this unusual new field.


State Transition Systems. Nondeterministic Transition Systems, Stochastic Transition Systems, and Quantum Transition Systems. The key issues: Exponentiality, Destructive Interference, Measurement. (1)

Review of Linear Algebra. Complex Inner Product Spaces. Eigenvalues and Eigenvectors, Diagonalisation. Tensor Products. (3)

Pure Quantum Mechanics. Quantum states. Unitary Evolution. Observables, Operators and Commutativity. Measurement. Simple Systems. The No-Cloning theorem. The Qubit. (3)

Entanglement. Schrodinger's cat. EPR states. Bell and CHSH Inequalities. The GHZ Argument. Basis copying versus cloning. (1)

Reading Week:

Computer Scientists and Joint CS and Maths: either Griffiths Chs 1-9 or Mermin Chs 1-4. Physicists, and Joint Maths and Phys: Brassard and Bratley Chs 1-4; other Mathematicians: either of the above. (2)

Basic quantum gates. Simple quantum algorithms. Quantum Teleportation. (3)

Examples Class (1)

Quantum Search (Grover's Algorithm). Quantum Fourier Transform. Phase estimation. Quantum Counting. (5)

Quantum Order Finding. Continued Fractions. Quantum Factoring (Shor's Algorithm). (3)

Teaching methods



Examples classes

Examples classes will be arranged as required

Feedback methods

Feedback is provided face to face or via email, in response to student queries regarding both the course exercises (5 formative exercise sheets with subsequently published answers) and the course material more generally.

Study hours

  • Lectures (24 hours)

Employability skills

  • Analytical skills
  • Innovation/creativity
  • Problem solving
  • Research

Learning outcomes

On successful completion of this unit, a student will be able to:

  • Use a subset of linear algebra to express quantum concepts.
  • Define concepts in quantum theory and be able to elicit the consequences of different quantum scenarios.
  • Interpret and analyse simple quantum circuits.

Reading list

Quantum computing for computer scientists Yanofsky, Noson S., 1967-9780521879965Cambridge University Press2008.
Principles of quantum computation and information Benenti, Giuliano.9812388583World Scientific2004.
Quantum computation and quantum information Nielsen, Michael A., 1974-9781107002173Cambridge University Press2010.

Additional notes

Course unit materials

Links to course unit teaching materials can be found on the School of Computer Science website for current students.