Quantum Computing Systems

MSRG investigates distributed quantum algorithms and quantum machine learning on today’s quantum hardware, using error mitigation to address device noise. We apply distributed computation to electronic-structure calculations and quantum learning methods to the search for useful chemical compounds.

These methods support practical scientific goals, including the discovery of catalysts that could help reduce greenhouse gases. We work with specialists such as synthetic inorganic chemists to connect computing research with chemical problems.

The group participates in Canada’s interdisciplinary Quantum Software Consortium, where Prof. Jacobsen serves as scientific director, and the University of Toronto’s Centre for Quantum Information and Quantum Control. These collaborations bring our distributed algorithms and machine learning expertise together with university researchers and industry partners.

Current directions

• Distributed quantum algorithms for electronic-structure calculations
• Error mitigation on current quantum devices
• Quantum machine learning for chemical discovery and catalyst research