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Suppression of crosstalk in superconducting qubits using dynamical decoupling

ORAL · Invited

Abstract

Currently available superconducting quantum processors with interconnected transmon qubits are noisy and prone to various errors. The errors can be attributed to sources such as open quantum system effects and spurious inter-qubit couplings (crosstalk). The ZZ-coupling between qubits in fixed frequency transmon architectures is always present and contributes to both coherent and incoherent crosstalk errors. Its suppression is therefore a key step towards enhancing the fidelity of quantum computation using transmons. Here we propose the use of dynamical decoupling to suppress the crosstalk and demonstrate the success of this scheme through experiments performed on several IBM quantum cloud processors. We demonstrate improvements in quantum memory as well as the performance of single-qubit and two-qubit gate operations. We perform open quantum system simulations of the multi-qubit processors and find good agreement with the experimental results. We analyze the performance of the protocol based on a simple analytical model and elucidate the importance of the qubit drive frequency in interpreting the results. We demonstrate that the XY4 dynamical decoupling sequence loses its universality if the drive frequency is not much larger than the system-bath coupling strength. Our work demonstrates that dynamical decoupling is an effective and practical way to suppress crosstalk and open system effects, thus paving the way towards higher-fidelity logic gates in transmon-based quantum computers.

Publication: Vinay Tripathi, Huo Chen, Mostafa Khezri, Ka-Wa Yip, E.M. Levenson-Falk, and Daniel A. Lidar, Phys. Rev. Applied 18, 024068 (2022)

Presenters

  • Vinay Tripathi

    University of Southern California

Authors

  • Vinay Tripathi

    University of Southern California

  • Huo Chen

    University of Southern California, Lawrence Berkeley National Laboratory

  • Mostafa Khezri

    Univ of Southern California, Google Quantum AI, Google LLC

  • Ka-Wa Yip

    University of Southern California

  • Eli Levenson-Falk

    Univ of Southern California

  • Daniel A Lidar

    University of Southern California