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Patrick Selig

Student

Project Title

Quantum Machine Learning

Project Description

Quantum computing is a potential game-changer as the field promises an exponential increase in computing power which will enable breakthrough applications in areas as diverse as vaccine and drug discovery, climate modelling, protein folding modelling, financial services and artificial intelligence among others. Equal 1 Laboratories Ireland Limited (Equal 1) is an innovative start-up creating a paradigm shift in quantum computing by developing disruptive, scalable and cost-effective quantum computing technology. Equal1 currently has a number of Quantum Computers operating at 3 kelvin with one currently on site at UCD that will be available for conducting experiments as part of this PhD project. A key goal would be the use of Variational hybrid quantum-classical algorithms. This class of algorithms enhance classical machine learning algorithms with quantum machine learning algorithms, for example quantum Boltzmann machines in which they are used to learn binary probability distributions. This type of algorithm is very promising for gaining an advantage over a classical computer in the Noisy Intermediate-Scale Quantum (NISQ) era, Different large-scale generative and optimization tasks in high impact domains (e.g. medical image processing) can be approached. The student will participate in a collaborative project with Equal1 to explore new data-driven and machine learning-based algorithms in the field of Quantum Artificial Intelligence. This will require the student to tackle open problems like the input problem and output problem, the comparison of gate based and adiabatic quantum computer and the analysis and an development of new approaches that make best use of the underlying hardware capabilities (e.g. native gates and their qubit connectivity, error characteristics).