The Toronto Intelligent Decision Engineering Laboratory
Quantum Computing

Hybrid Quantum-Classical Computing Algorithms


Members

J. Christopher Beck
Tony T. Tran

Project description

Quantum computing is a technology with the potential to provide a significant speedup over classical computing for some combinatorial optimization problems. However, due to the relatively early stage of research and development regarding quantum computers, there are many limitations of the technology. Our work considers hybrid quantum-classical algorithms that improve upon the scalability and applicability of quantum computing. This work represents the first implementation of a hybrid quantum-classical algorithm on real quantum hardware and is a collaborative effort with the Quantum Artificial Intelligence Laboratory (https://ti.arc.nasa.gov/tech/dash/physics/quail/) and the Planning and Scheduling Group (https://ti.arc.nasa.gov/tech/asr/planning-and-scheduling/) at NASA Ames Research Center.

Start date

June 2015

Publications

  1. Tran, T.T., Do, M., Rieffel, E., Frank, J., Wang, Z., O'Gorman, B., Venturelli, D., & Beck, J.C., "A Hybrid Quantum-Classical Approach to Solving Scheduling Problems", Proceedings of the Symposium on Combinatorial Search, (SOCS2016), 98-106, 2016.
  2. Tran, T.T., Wang, Z., Do, M., Rieffel, E., Frank, J., O'Gorman, B., Venturelli, D., & Beck, J.C., "Explorations of Quantum-Classical Approaches to Scheduling a Mars Lander Activity Problem", Proceedings of the AAAI 2016 Workshop on Planning for Hybrid Systems (PlanHS-16), 2016.

University of Toronto Mechanical and Information Engineering