The researcher from UKZN’s Centre for Quantum Technology was named as a runner up in the competition for her paper Implementing a Distance-Based Classifier with a Quantum Interference Circuit. The paper was published in Europhysics Letters and was co-authored by Mr Mark Fingerhuth and Professor Francesco Petruccione.
Prizes were awarded for the highest-impact scientific papers by a master’s student, PhD student or postdoctoral researcher using the IBM Q Experience and Qiskit as tools to achieve the presented results.
The aim of the competition for the IBM Q best paper award is to encourage more teachers and students to take advantage of the cloud-based quantum computer, the IBM Q Experience, and the IBM Qiskit development platform and move into the world of quantum computing, which enters the “spooky” world of quantum mechanics.
The IBM Q Experience is designed to provide quantum researchers with the support, collaboration and tooling they need to do high quality work, and remove hurdles as they enter quantum computing.
Schuld explained: ‘In our paper, we propose that quantum machine learning should be thought of from the direction of quantum circuits which lead to classifiers, instead of the other way around.’ ‘We implemented a proof-of-principle experiment with the IBM Q Experience, and together with numerical simulations, showed that this classifier works surprisingly well in simple benchmarks, providing a minimal example of a quantum machine learning algorithm that can be implemented and understood by beginners to quantum computing.’
‘We are very happy and proud that Dr Maria Schuld is one of the winners,’ said Petruccione of the Centre for Quantum Technology.
Schuld, who is from Germany, visited South Africa during her bachelor’s studies at the Technical University of Berlin for an internship with the Centre for Quantum Technology, and eventually settled in Durban where she completed her PhD studies through UKZN. For her PhD studies, she followed on from her master’s work on the development of quantum models for biological neural networks, and she pursued doctoral research on the topic of the development of machine learning algorithms for quantum computers.
Schuld’s current research is centred on quantum machine learning. She has also recently published a book titled Supervised learning with quantum computers, which she co-authored with Petruccione.
Schuld’s field was also the focus of the Quantum Techniques in Machine Learning conference hosted by the Centre in Durban in November.
She is now focusing on variational circuits, which she explained as causing a quantum device to learn how to compute from data. This could be used to explore an altogether new class of machine learning models based on quantum information. She said the new field, while unexplored, is generating excitement within this research community.
Words: Christine Cuénod
Photograph: Supplied by Maria Schuld