Quantum Machine Learning

Quantum Machine Learning (QML) is a nascent and yet remarkably promising field. It is the attempt to combine the insights of classical artificial intelligence with the potential performance boosts that quantum computing may offer. For example, this can take the form of obtaining quantum speedups over the best classical algorithms, an approach that has already found interesting results, or of constructing quantum algorithms that perform tasks no classical machine learning algorithm could. Quantum Machine Learning also investigates the generalisation performance of quantum algorithms, especially of those that can run on early-stage quantum hardware. Variational Circuits, a powerful example thereof, are the primary architectures focused on at UKZN, allowing for implementations of quantum neural networks and kernel functions. Another strongly related field pursued within the Quantum Research Group at UKZN is the analysis of quantum data with either classical or quantum AI architectures.