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Real-time quantum error correction beyond break-even

Author

Listed:
  • V. V. Sivak

    (Yale University
    Yale University
    Yale University
    Google AI Quantum)

  • A. Eickbusch

    (Yale University
    Yale University
    Yale University)

  • B. Royer

    (Yale University
    Yale University
    Yale University
    Université de Sherbrooke)

  • S. Singh

    (Yale University
    Yale University
    Yale University)

  • I. Tsioutsios

    (Yale University
    Yale University
    Yale University)

  • S. Ganjam

    (Yale University
    Yale University
    Yale University)

  • A. Miano

    (Yale University
    Yale University
    Yale University)

  • B. L. Brock

    (Yale University
    Yale University
    Yale University)

  • A. Z. Ding

    (Yale University
    Yale University
    Yale University)

  • L. Frunzio

    (Yale University
    Yale University
    Yale University)

  • S. M. Girvin

    (Yale University
    Yale University
    Yale University)

  • R. J. Schoelkopf

    (Yale University
    Yale University
    Yale University)

  • M. H. Devoret

    (Yale University
    Yale University
    Yale University)

Abstract

The ambition of harnessing the quantum for computation is at odds with the fundamental phenomenon of decoherence. The purpose of quantum error correction (QEC) is to counteract the natural tendency of a complex system to decohere. This cooperative process, which requires participation of multiple quantum and classical components, creates a special type of dissipation that removes the entropy caused by the errors faster than the rate at which these errors corrupt the stored quantum information. Previous experimental attempts to engineer such a process1–7 faced the generation of an excessive number of errors that overwhelmed the error-correcting capability of the process itself. Whether it is practically possible to utilize QEC for extending quantum coherence thus remains an open question. Here we answer it by demonstrating a fully stabilized and error-corrected logical qubit whose quantum coherence is substantially longer than that of all the imperfect quantum components involved in the QEC process, beating the best of them with a coherence gain of G = 2.27 ± 0.07. We achieve this performance by combining innovations in several domains including the fabrication of superconducting quantum circuits and model-free reinforcement learning.

Suggested Citation

  • V. V. Sivak & A. Eickbusch & B. Royer & S. Singh & I. Tsioutsios & S. Ganjam & A. Miano & B. L. Brock & A. Z. Ding & L. Frunzio & S. M. Girvin & R. J. Schoelkopf & M. H. Devoret, 2023. "Real-time quantum error correction beyond break-even," Nature, Nature, vol. 616(7955), pages 50-55, April.
  • Handle: RePEc:nat:nature:v:616:y:2023:i:7955:d:10.1038_s41586-023-05782-6
    DOI: 10.1038/s41586-023-05782-6
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    Citations

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    Cited by:

    1. Suhas Ganjam & Yanhao Wang & Yao Lu & Archan Banerjee & Chan U Lei & Lev Krayzman & Kim Kisslinger & Chenyu Zhou & Ruoshui Li & Yichen Jia & Mingzhao Liu & Luigi Frunzio & Robert J. Schoelkopf, 2024. "Surpassing millisecond coherence in on chip superconducting quantum memories by optimizing materials and circuit design," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Bingzhi Zhang & Junyu Liu & Xiao-Chuan Wu & Liang Jiang & Quntao Zhuang, 2024. "Dynamical transition in controllable quantum neural networks with large depth," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    3. Xin Meng & Youwei Zhang & Xichang Zhang & Shenchao Jin & Tingran Wang & Liang Jiang & Liantuan Xiao & Suotang Jia & Yanhong Xiao, 2023. "Machine learning assisted vector atomic magnetometry," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    4. Axel M. Eriksson & Théo Sépulcre & Mikael Kervinen & Timo Hillmann & Marina Kudra & Simon Dupouy & Yong Lu & Maryam Khanahmadi & Jiaying Yang & Claudia Castillo-Moreno & Per Delsing & Simone Gasparine, 2024. "Universal control of a bosonic mode via drive-activated native cubic interactions," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    5. Yao Lu & Aniket Maiti & John W. O. Garmon & Suhas Ganjam & Yaxing Zhang & Jahan Claes & Luigi Frunzio & Steven M. Girvin & Robert J. Schoelkopf, 2023. "High-fidelity parametric beamsplitting with a parity-protected converter," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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