

Large scale simulations of photonic quantum computers
Current quantum computers are in the “NISQ”, or Noisy-Intermediate-Scale-Quantum regime. The true potential of quantum computing will only be realized when noise levels are reduced or controlled, and large scale is achieved. Xanadu’s approach is to use photonic technology as the building blocks of their machines. This project addresses the question: How do we build a useful quantum computer based on imperfect photonics components? There are 2 specific aspects of this general question: A – In which conditions does a photonic quantum computer reach quantum advantage (demonstrating large speedups compared to today’s most powerful conventional computers)? B – What are the resources required to build a scalable fault-tolerant photonic quantum computer? This project will provide the team with a much more detailed understanding of the requirements and tradeoffs involved in the future, much larger-scale generations of quantum photonic hardware that must be built in order to fully realize the theoretical potential of quantum computing.By mapping out a pathway to demonstrating quantum advantage, and large-scale, fault-tolerant quantum computing, this project will guide Xanadu’s ongoing efforts to build more powerful quantum computers which can deliver commercial benefits to customers and ensure economic impact.
Industry Partner(s): Xanadu Quantum Technologies Inc.
Academic Institution: University of Toronto
Academic Researcher: John Sipe
Platform: GPU, Parallel CPU
Focus Areas: Advanced Manufacturing, ICT

Smart Handling of Big Radio Signal Data
This project will take advantage of some of the world’s largest data sets produced by radio astronomy, established University of Toronto and Ontario astronomy expertise, and technology from IBM to strengthen IBM Canada’s position in the upcoming generation of big projects including signal processing for ALMA (Atacama Large Millimeter/submillimeter Array) and SKA (Square Kilometer Array).
Industry Partner(s): IBM Canada Ltd.
Academic Institution: University of Toronto
Academic Researcher: Ue-Li Pen
Focus Areas: ICT