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Creation, verification, and scalability of decoherence-free subspaces and noiseless subsystems on superconducting qubits

ORAL

Abstract

Decoherence-free subspaces/noiseless subsystems (DFS/NS) preserve quantum information by identifying subspaces/subsystems of the Hilbert space that remain unaffected by decoherence. Identifying DFS/NS codes under collective decoherence is well-understood, and the resultant codes support scalable and universal quantum computation. While most experimental systems, including superconducting qubit-based devices, do not decohere collectively, it is possible to engineer the conditions for collective decoherence using dynamical decoupling (DD) sequences. We report on the creation and verification of DD assisted DFS/NS codes on quantum processors provided by the IBM Quantum Experience. We compare the performance of a DFS/NS encoded qubit with its unprotected counterpart. We show that qubit lifetime can be improved substantially using DD assisted DFS/NS codes. Furthermore, we exploit gate set tomography to characterize logical error channels and estimate logical gate error rates for the DFS/NS encoding. When combined with an analysis of qubit lifetimes for multiple simultaneously encoded qubits, we obtain a comprehensive picture of DFS/NS feasibility and scalability on near-term quantum processors.

Presenters

  • Bibek Pokharel

    Univ of Southern California, University of Southern California

Authors

  • Gregory Quiroz

    Johns Hopkins University Applied Physics Laboratory, Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Lab

  • Bibek Pokharel

    Univ of Southern California, University of Southern California

  • Yifan Sun

    Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences

  • Joseph Boen

    Johns Hopkins University Applied Physics Laboratory

  • Lina Tewala

    Johns Hopkins University Applied Physics Laboratory, Applied Phys Lab/JHU

  • Vinay Tripathi

    University of Southern California

  • Matthew Kowalsky

    University of Southern California, Univ of Southern California

  • Devon Williams

    Johns Hopkins University Applied Physics Laboratory

  • Jun-Yi Zhang

    King Abdullah Univ of Sci & Tech (KAUST)

  • Paraj Titum

    APL, Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Laboratory

  • Lian-Ao Wu

    University of the Basque Country

  • Kevin Schultz

    Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Laboratory, Johns Hopkins University Applied Physics Lab

  • Daniel Lidar

    Univ of Southern California, University of Southern California