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Generation of genuine entanglement up to 51 superconducting qubits

Author

Listed:
  • Sirui Cao

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Bujiao Wu

    (Peking University
    Peking University)

  • Fusheng Chen

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Ming Gong

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Yulin Wu

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Yangsen Ye

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Chen Zha

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Haoran Qian

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Chong Ying

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Shaojun Guo

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Qingling Zhu

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • He-Liang Huang

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Youwei Zhao

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Shaowei Li

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Shiyu Wang

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Jiale Yu

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Daojin Fan

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Dachao Wu

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Hong Su

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Hui Deng

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Hao Rong

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Yuan Li

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Kaili Zhang

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Tung-Hsun Chung

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Futian Liang

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Jin Lin

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Yu Xu

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Lihua Sun

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Cheng Guo

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Na Li

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Yong-Heng Huo

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Cheng-Zhi Peng

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Chao-Yang Lu

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Xiao Yuan

    (University of Science and Technology of China
    Peking University
    Peking University)

  • Xiaobo Zhu

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

  • Jian-Wei Pan

    (University of Science and Technology of China
    University of Science and Technology of China
    University of Science and Technology of China)

Abstract

Scalable generation of genuine multipartite entanglement with an increasing number of qubits is important for both fundamental interest and practical use in quantum-information technologies1,2. On the one hand, multipartite entanglement shows a strong contradiction between the prediction of quantum mechanics and local realization and can be used for the study of quantum-to-classical transition3,4. On the other hand, realizing large-scale entanglement is a benchmark for the quality and controllability of the quantum system and is essential for realizing universal quantum computing5–8. However, scalable generation of genuine multipartite entanglement on a state-of-the-art quantum device can be challenging, requiring accurate quantum gates and efficient verification protocols. Here we show a scalable approach for preparing and verifying intermediate-scale genuine entanglement on a 66-qubit superconducting quantum processor. We used high-fidelity parallel quantum gates and optimized the fidelitites of parallel single- and two-qubit gates to be 99.91% and 99.05%, respectively. With efficient randomized fidelity estimation9, we realized 51-qubit one-dimensional and 30-qubit two-dimensional cluster states and achieved fidelities of 0.637 ± 0.030 and 0.671 ± 0.006, respectively. On the basis of high-fidelity cluster states, we further show a proof-of-principle realization of measurement-based variational quantum eigensolver10 for perturbed planar codes. Our work provides a feasible approach for preparing and verifying entanglement with a few hundred qubits, enabling medium-scale quantum computing with superconducting quantum systems.

Suggested Citation

  • Sirui Cao & Bujiao Wu & Fusheng Chen & Ming Gong & Yulin Wu & Yangsen Ye & Chen Zha & Haoran Qian & Chong Ying & Shaojun Guo & Qingling Zhu & He-Liang Huang & Youwei Zhao & Shaowei Li & Shiyu Wang & J, 2023. "Generation of genuine entanglement up to 51 superconducting qubits," Nature, Nature, vol. 619(7971), pages 738-742, July.
  • Handle: RePEc:nat:nature:v:619:y:2023:i:7971:d:10.1038_s41586-023-06195-1
    DOI: 10.1038/s41586-023-06195-1
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    Citations

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    Cited by:

    1. Jieshan Huang & Xudong Li & Xiaojiong Chen & Chonghao Zhai & Yun Zheng & Yulin Chi & Yan Li & Qiongyi He & Qihuang Gong & Jianwei Wang, 2024. "Demonstration of hypergraph-state quantum information processing," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Zehang Bao & Shibo Xu & Zixuan Song & Ke Wang & Liang Xiang & Zitian Zhu & Jiachen Chen & Feitong Jin & Xuhao Zhu & Yu Gao & Yaozu Wu & Chuanyu Zhang & Ning Wang & Yiren Zou & Ziqi Tan & Aosai Zhang &, 2024. "Creating and controlling global Greenberger-Horne-Zeilinger entanglement on quantum processors," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    3. Wang, Shaoxuan & Shen, Yingtong & Liu, Xinjian & Zhang, Haoying & Wang, Yukun, 2024. "Variational quantum entanglement classification discrimination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    4. Kevin He & Ming Yuan & Yat Wong & Srivatsan Chakram & Alireza Seif & Liang Jiang & David I. Schuster, 2024. "Efficient multimode Wigner tomography," Nature Communications, Nature, vol. 15(1), pages 1-7, December.

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