The goal of this research is to demonstrate that existing and near-term (5-8 years) quantum computing (QC) technologies can be used to generate meaningful computational results of scientic and/or commercial value that cannot be efficiently obtained through classical computation alone. It will approach this through a unique-to-QMI coordinated effort to develop novel strategies for using present day (NISQ-era) QC hardware. We will focus on:
- Fundamental quantum computing theory relevant to the potential use of symmetry and topological properties of quantum states
- The experimental realization of novel quantum hardware designed to carry out special purpose quantum simulations, and
- The integration of 1 and 2, along with conventional quantum and classical programming, into a hybrid approach employing Bayesian machine learning. The utility of these novel strategies will be tested by applying them to solve a select set of scientifically important problems, chosen mostly from the field of Quantum Materials.
Once validated in specific applications, the QC techniques we develop should be generally applicable to a wide range of other engineering, economic, medical and materials problems.
This project is launched by SBQMI as a part of the Grand Challenge program.
Project webpage: https://qmi.ubc.ca/grand-challenges/quantum-computing