Quantum Computing

Since the 1960s, technological advances have enabled silicon transistors to keep shrinking, causing computational capability to grow exponentially. However, transistors cannot shrink much further; they are already so small that the laws of quantum mechanics begin to impair their performance. This is already starting to limit our society’s breakthroughs in certain fields as diverse as the design and discovery of new chemicals (enzymes for carbon capture, fertilizers, dyes), new materials (room temperature superconductors, batteries), and the development of new medicines and drugs; machine learning, and artificial intelligence.

Fortunately, quantum mechanical behaviour opens amazing new possibilities for computation. A well-developed theory for a radically new Quantum Information Technology proves that computers that rely fundamentally on quantum mechanics can potentially solve many important computational problems that will remain forever intractable using conventional computers. The international race for quantum computing has attracted enormous research funding including $1B over 10 years in Europe, $4B over 5 years in China, and hundreds of millions by several multinational companies including Microsoft, Google, IBM, and Intel.

The grand challenge for the Quantum Computing Cluster (QCC) is to develop technologies for, and to explore applications in, quantum computing that will enable the solving some of the world’s most challenging problems. Specifically, our goal is to develop the next generation quantum information technologies with the goal of developing a universal quantum computer that is demonstrably scalable to achieve a quantum advantage over classical computers. In parallel, we will be to conduct research with existing quantum processor technologies. Our cluster will help incubate a `Quantum Silicon Valley’, namely a local ecosystem of companies commercializing the next generation quantum computers, with all the necessary ingredients (machine learning algorithms, software) to solve meaningful and impactful real-world problems.

The specific research themes and skills that are required to build such a computer, and the team working on solving these includes:


Next generation quantum computing hardware:

  • Fundamental quantum research: Fundamental theory: qubit circuit architectures, measurement based quantum computing, error correction and fault tolerant design, decoherence, spin-based qubit dynamics, quantum Ising systems (Robert Raussendorf UBC/Physics, Philip Stamp UBC/Physics).
  • Implementations of individual qubits (akin to transistors):
    • 1. Donor atom spin-based qubits in silicon photonic resonators (Stephanie Simmons SFU/Physics, Michael Thewalt SFU/Physics, Jeff Young UBC/Physics, Lukas Chrostowski UBC/Electrical and Computer Engineering),
    • 2. Majorana particles and topological materials (Josh Folk UBC/Physics),
    • 3. Quantum-dot cellular automata (QCA) using atomic silicon dangling bond surface states  (Konrad Walus UBC/Electrical and Computer Engineering,
    • 4. Trapped electrons in vacuum (Alireza Nojeh UBC/Electrical and Computer Engineering).
    • 5. Novel atom-based qubits in silicon for circuit quantum electrodynamics (Joe Salfi UBC/Electrical and Computer Engineering)
  • Quantum simulators (Joe Salfi UBC/Electrical and Computer Engineering)

Technologies required to initialize, control, entangle, and readout the qubits (akin to circuits):

  • photonics (Lukas Chrostowski, Jeff Young, Nicolas Jaeger UBC/Electrical and Computer Engineering, David Jones UBC/Physics, Simmons),
  • cryogenic CMOS and superconducting electronics (Sudip Shekhar UBC/Electrical and Computer Engineering, Shahriar Mirabbasi UBC/Electrical and Computer Engineering, Joe Salfi UBC/Electrical and Computer Engineering),
  • cryogenic packaging and mechanical design (Mu Chiao UBC/Mechanical Engineering).

Software and Computer Engineering:

  • QC compilers, QC simulators, QC architectures (Konrad Walus, Tor Aamodt, Prashant Nair UBC/Electrical and Computer Engineering, Lumerical Solutions Inc.),
  • converting applications/problems into physical qubit computer code, optimization, algorithms (Steve Wilton UBC/Electrical and Computer Engineering, Michael Friedlander UBC/Computer Science/Mathematics),
  • machine learning, deep learning (Tor Aamodt, Bhushan Gopaluni UBC/Chemical and Biological Engineering),
  • architecture-level techniques to enable reliable qubits, investigating efficient control computer designs (Prashant Nair, UBC/Electrical and Computer Engineering).

Applications and societal impacts of QC:

  • molecules, chemistry (Roman Krems UBC/Chemistry),
  • quantum materials (Joe Salfi UBC/Electrical and Computer Engineering)
  • deep learning chemoinformatics for drug discovery and other chemical design (William Macready D-Wave),
  • weather forecasting (Roland Stull UBC/Earth, Ocean and Atmospheric Sciences), and
  • detecting changes in the brain as a result of concussions using EEG signals (Naznin Virji-Babul, UBC/Medicine/Centre for Brain Health).
  • We will specifically focus on application areas where quantum computing will make an impact.

Our researchers collaborate on Quantum Computing with D-Wave Systems1QbitQuantum SiliconMicrosoft, and Lumerical Solutions Inc.



  • October 2017: Silicon Quantum Leap (SiQL), $19M Canadian Foundation for Innovation grant, awarded to SFU-UBC team: “Blasting past computer limits – In Vancouver, researchers aim to build the world’s first universal quantum computer and open up entirely new possibilities” CFI news,  SFU news story.



Next generation quantum computing hardware
Technologies required to initialize, control, entangle, and readout the qubits
Software and Computer Engineering
Applications and societal impacts of QC