University of Waterloo

Published purpose

The Project employs modern machine learning to accelerate the development of industry-ready quantum computing technologies. To this end, the Project addresses the key bottleneck in quantum computing technologies, quantum errors, by pioneering advancements in quantum error prevention and correction through machine learning methods. Machine learning methods, and in particular transformers, possess the potential to learn and model the patterns and dynamics of quantum errors in individual quantum processor hardware in unprecedented detail and with unprecedented adaptability to individual quantum processors. This opens the prospect of machine-learned quantum error handling strategies that are significantly more complex, and efficient, than the more rigid manually developed methods currently in use. By fundamentally transforming the approach to quantum error handling, the Project will accelerate the transition from experimental quantum systems to reliable, scalable quantum computing platforms, aiming to ensure a leading edge for Canada in the global technological landscape