Research Area

Quantum Computing Systems

Our research in quantum computing focuses on distributed algorithms and quantum machine learning using the current generation of quantum devices with state-of-the-art error mitigation techniques. One central aspect of our work is applying these algorithms to accelerate electronic structure theory calculations through distributed quantum algorithms and to explore chemical compound space with quantum machine learning. An important aspect of this work is to solve real-world problems, such as finding catalysts for greenhouse gas reduction, in collaboration with domain experts, such as synthetic inorganic chemists.

To this aim, we are involved with the interdisciplinary Quantum Software Consortium in Canada, with Prof. Jacobsen being the scientific director, and the Centre for Quantum Information and Quantum Control at the University of Toronto. Through these interdisciplinary initiatives, we are combining our domain expertise in distributed algorithms and machine learning with experts at the University of Toronto and industry partners to solve real-world problems using state-of-the-art quantum algorithms.