Noisy Intermediate Scale Quantum (NISQ) Computing

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:

  1. Fundamental quantum computing theory relevant to the potential use of symmetry and topological properties of quantum states
  2. The experimental realization of novel quantum hardware designed to carry out special purpose quantum simulations, and
  3. 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


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