Efficient online quantum gate set diagnosis by Fast-Bayesian Tomography

ORAL

Abstract

To push the error rate closer to the threshold for fault-tolerate quantum computing, it is critical to characterise the gate error and fix them actively. Harnessed the power of Bayesian approach, Fast Bayesian Tomography (FBT) is a self-consistent process tomography technique, which is experimentally flexible and computationally efficient. In this work, we demonstrate the experimental approach of running the FBT online, which allows the model to be updated as experiment data obtained. Various improvements have been achieved to make the protocol even more efficient and experimentally low-cost. We are also showing the practical diagnosis applications of the FBT protocol on our 2 qubit system based on silicon quantum dots.

*Funding: The authors acknowledge support from the Australian Research Council (DE190101397, FL190100167 and CE170100012), the US Army Research Office (W911NF17-1-0198) and the NSW Node of the Australian National Fabrication Facility. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the US Government. R.S acknowledge support from Sydney Quantum Academy. The authors thank Kohei Itoh for the preparation of the isotopically-purified silicon substrate.

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Presenters

  • Yue Su

    • University of New South Wales

Authors

  • Yue Su

    • University of New South Wales

  • Yue Y Huang

    • UNSW
    • 1) University of New South Wales
    • University of New South Wales

  • MengKe Feng

    • University of New South Wales
    • 1) University of New South Wales

  • Nard Dumoulin Stuyck

    • UNSW
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.

  • Tuomo I Tanttu

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales 2) Diraq
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.

  • Andre Saraiva

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.
    • UNSW Sydney
    • UNSW
    • Diraq
    • University of New South Wales, Diraq Pty. Ltd.

  • Henry Yang

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.
    • UNSW Sydney

  • Wee Han Lim

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.
    • University of New South Wales

  • Kok Wai Chan

    • 1) University of New South Wales, 2) Diraq Pty. Ltd.

  • William Gilbert

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.

  • Fay E Hudson

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.
    • University of New South Wales

  • Arne Laucht

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.
    • University of New South Wales
    • University of New South Wales, Diraq Pty. Ltd.

  • Andrew S Dzurak

    • 1) University of New South Wales, 2) Diraq Pty. Ltd
    • 1) University of New South Wales, 2) Diraq Pty. Ltd.
    • University of New South Wales
    • University of New South Wales, Diraq Pty. Ltd.