H9QC - Quantum Computing

Module Code: H9QC
Long Title Quantum Computing
Title Quantum Computing
Module Level: LEVEL 9
EQF Level: 7
EHEA Level: Second Cycle
Credits: 5
Module Coordinator: Horacio Gonzalez-Velez
Module Author: MICHAEL BRADFORD
Departments: School of Computing
Specifications of the qualifications and experience required of staff

This module requires a lecturer holding a Master’s degree or higher, in a discipline with a significant programming/mathematics component. e.g. Computer Science, Mathematics, Computational Physics. Lecturer: Mr. Michael Bradford
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Interpret and apply mathematical and quantum mechanical principles to qubit systems.
LO2 Critically assess the similarities and differences between quantum and classical computation.
LO3 Analyse computational problems and formulate solutions through the implementation of algorithms for quantum computers.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Entry requirements

A cognate level 8 degree.
 

Module Content & Assessment

Indicative Content
Introduction
Results from the theory of quantum mechanics. Spin and polarization. Measurements/Observables. Randomness and probability. Bits and Qubits. Quantum parallelism and interference.
Linear Vector Spaces and Hilbert Spaces
Review of linear spaces.. Hilbert spaces. Dirac notation. Operations and operators.
Matrix Representations
The Bloch Sphere. Pauli Matrices. Orthogonal and unitary matrices. Operations and operators. Eigenvectors and eigenvalues.
Quantum Circuits
Logic Gates. Reversibility. Multi-qubit Gates. Diagrammatic representation. Deutsch’s Algorithm.
Programming for Quantum Computing
Programming environments. Language support. Simulation. Quantum Computing cloud services.
Entanglement
Entangled states. Bell’s Inequalities. Using the CNOT gate. No Cloning Theorem. Quantum Teleportation.
Applications
Quantum Cryptography. Quantum Key Distribution. Ekert Protocol. BB48 Protocol. Dense coding.
Quantum Fourier Transform
Fourier Series. Discrete Fourier Transform. Quantum Fourier Transform.
Quantum Algorithms
Deutsch-Josza Algorithm. Simon’s Algorithm.
Quantum Algorithms
Grover’s Search Algorithm.
Quantum Algorithms
Schor’s Algorithm.
Ramifications of Quantum Computing
Quantum Hardware. Quantum Supremacy. Data Security.
Assessment Breakdown%
Coursework40.00%
End of Module Assessment60.00%

Assessments

Full Time

Coursework
Assessment Type: Continuous Assessment % of total: 40
Assessment Date: Week 8 Outcome addressed: 1,3
Non-Marked: No
Assessment Description:
Design and implement a QC circuit to model and solve problems.
Assessment Type: Formative Assessment % of total: Non-Marked
Assessment Date: n/a Outcome addressed: 1,2,3
Non-Marked: Yes
Assessment Description:
Formative assessment will be undertaken utilising exercises and short answer questions during certain tutorials.  In class discussions will be undertaken on contemporary topics. Feedback will be provided individually or as a group in oral format.
End of Module Assessment
Assessment Type: Terminal Exam % of total: 60
Assessment Date: End-of-Semester Outcome addressed: 1,2,3
Non-Marked: No
Assessment Description:
n/a
No Workplace Assessment
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
Reassessment Description
Learners who fail this module will be required to sit a repeat examination where all learning outcomes will be examined.

NCIRL reserves the right to alter the nature and timings of assessment

 

Module Workload

Module Target Workload Hours 0 Hours
Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Classroom & Demonstrations (hours) 24 Every Week 24.00
Tutorial Other hours (Practical/Tutorial) 24 Every Week 24.00
Independent Learning Independent learning (hours) 77 Every Week 77.00
Total Weekly Contact Hours 48.00
 

Module Resources

Recommended Book Resources
  • Michael A. Nielsen,Isaac L. Chuang. (2010), Quantum Computation and Quantum Information, Cambridge University Press, p.702, [ISBN: 9781107002173].
  • Bernard Zygelman. (2018), A First Introduction to Quantum Computing and Information, Springer, p.233, [ISBN: 3319916289].
  • N. David Mermin. (2007), Quantum Computer Science, Cambridge University Press, p.233, [ISBN: 0521876583].
Supplementary Book Resources
  • Chris Bernhardt. (2019), Quantum Computing for Everyone, MIT Press, p.216, [ISBN: 0262039257].
This module does not have any article/paper resources
This module does not have any other resources
Discussion Note: