Quantum computing is an interdisciplinary field that lies at the intersection of computer science, mathematics, and physics. This computational paradigm relies on principles of quantum mechanics, such as superposition and entanglement, to obtain powerful algorithms.
This module aims to provide a selfcontained, comprehensive introduction to quantum computing, focusing on the design and analysis of quantum algorithms, as well as covering topics in quantum information and quantum cryptography, such as: quantum teleportation, quantum money, and postquantum cryptography.
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Quantum computing — motivation, foundations, and prominent applications.
Review of linear algebra in the context of quantum information, Dirac’s bracket notation, limitation of classical algorithms.
The four postulates of quantum mechanics, qubits, quantum gates and circuits.
Basic quantum algorithms I — Deutsch’s algorithm, analysing quantum algorithms, and implementing quantum circuits via QISKIT.
Basic quantum algorithms II — Simon’s problem and the Bernstein Vazirani algorithm.
Grover’s quantum search algorithm, the BBBV Theorem, and applications of Grover’s algorithm.
RSA, and Shor’s integer factorisation algorithm.
Introduction to quantum cryptography (postquantum security, quantum key distribution).
Introduction to quantum information (superdense coding, nocloning theorem, quantum teleportation) Applications (quantum money, the ElitzurVaidman bomb).
By the end of the module, students should be able to:
Please see Talis Aspire link for most up to date list.
View reading list on Talis Aspire
Designing and analysing quantum algorithms.
Understanding quantum mechanics and the power of quantum computing.
Type  Required 

Lectures  30 sessions of 1 hour (20%) 
Seminars  10 sessions of 1 hour (7%) 
Private study  110 hours (73%) 
Total  150 hours 
Revising linear algebra, the postulates of quantum mechanics, the principles of superposition, measurement, and entanglement. Analysing the algorithm discussed in class, including: Deutsch’s algorithm, the DeutschJosza algorithm, the BersteinVazirani algorithm, Grover’s algorithm, Simon’s algorithm, and Shor’s algorithm.
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Students can register for this module without taking any assessment.
Weighting  Study time  

Problem Set 1  10%  
Problem Set 1. This assessment is eligible for selfcertification (extension). 

Problem Set 2  10%  
Problem Set 2. This assessment is eligible for selfcertification (extension). 

Problem Set 3  10%  
Problem Set 3. This assessment is eligible for selfcertification (extension). 

Inperson Examination  70%  
CS939 examination

Weighting  Study time  

Inperson Examination  Resit  100%  
CS939 MSc resit examination

Comments on assignments alongside a mark will be provided, solutions will be discussed in the seminars.
This module is Optional for: