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Algorithm-specific Performance Analysis of Transmon Qubit Devices

ORAL

Abstract

Many demonstrations of quantum algorithms exhibit a tradeoff between the accuracy of the algorithm and the fidelity of the circuit that implements that algorithm. In particular, for algorithms that rely on Trotter decomposition to approximate a target unitary, increasing the number of steps reduces the algorithm error. However, in current devices, uncontrolled interactions with the environment and suboptimal control limit qubit coherence and gate fidelity, which ultimately restrict circuit depth. We analyze algorithm performance on transmon qubit devices using simulated, model-based, and experimentally measured process maps for gates, and compare a number of characterization metrics. In the case of a Trotterized algorithm, we determine the optimal operating point and predict the expected performance in good agreement with experiment.

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Presenters

  • Michael O'Keeffe

    MIT Lincoln Laboratory

Authors

  • Michael O'Keeffe

    MIT Lincoln Laboratory

  • Morten Kjaergaard

    Research Laboratory of Electronics, Massachusetts Institute of Technology MIT, Massachusetts Institute of Technology MIT, Research Laboratory of Electronics, Massachusetts Institute of Technology, Massachusetts Institute of Technology

  • Mollie Schwartz

    MIT Lincoln Laboratory, MIT Lincoln Lab

  • Gabriel Orr Samach

    MIT Research Laboratory of Electronics, MIT Department of Electrical Engineering and Computer Science, MIT Lincoln Laboratory, Massachusetts Institute of Technology, MIT Lincoln Laboratory, Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT, Massachusetts Institute of Technology, Research Laboratory of Electronics, Massachusetts Institute of Technology, MIT Lincoln Laboratory

  • Amy Greene

    Massachusetts Institute of Technology MIT, Massachusetts Institute of Technology, Research Laboratory of Electronics, Massachusetts Institute of Technology

  • Chris McNally

    Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT, Research Laboratory of Electronics, Massachusetts Institute of Technology

  • Danna Rosenberg

    MIT Lincoln Laboratory, MIT Lincoln Lab, MIT Lincoln Laboratories, Massachusetts Institute of Technology

  • William Oliver

    Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Department of Physics, MIT Lincoln Laboratory, Massachusetts Institute of Techn, MIT Lincoln Lab, MIT Lincoln Laboratory, MIT Lincoln Laboratory, Massachusetts Institute of Technology, Department of Physics, Department of Electrical Engineering and Computer Science, Research Laboratory of Electronics, Lincoln Laboratory, Massachusetts Institute of Technology, Research Laboratory of Electronics, Massachusetts Institute of Technology MIT, Massachusetts Institute of Technology MIT, Department of Electrical Engineering and Computer Science, Department of Physics, Massachusetts Institute of Technology; MIT Lincoln Laboratory, Department of Electrical Engineering and Computer Science, Department of Physics, MIT Lincoln Laboratory, Massachusetts Institute of Technology, Massachusetts Institute of Technology, Research Laboratory of Electronics, Massachusetts Institute of Technology, Research Laboratory of Electronics, Department of Electrical Engineering & Computer Science, Department of Physics, Massachusetts Institute of Technology and MIT Lincoln Labo, Physics, MIT, MIT-Lincoln Lab, MIT Lincoln Laboratories, Research Laboratory of Electronics, Department of Physics, Department of Electrical Engineering and Computer Science, Lincoln Laboratory, Massachusetts Institute of Technolog

  • Andrew James Kerman

    MIT Lincoln Laboratory

  • Kevin Obenland

    MIT Lincoln Laboratory