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Deep quantum neural networks on a superconducting processor

Author

Listed:
  • Xiaoxuan Pan

    (Tsinghua University)

  • Zhide Lu

    (Tsinghua University)

  • Weiting Wang

    (Tsinghua University)

  • Ziyue Hua

    (Tsinghua University)

  • Yifang Xu

    (Tsinghua University)

  • Weikang Li

    (Tsinghua University)

  • Weizhou Cai

    (Tsinghua University)

  • Xuegang Li

    (Tsinghua University)

  • Haiyan Wang

    (Tsinghua University)

  • Yi-Pu Song

    (Tsinghua University)

  • Chang-Ling Zou

    (University of Science and Technology of China
    Hefei National Laboratory)

  • Dong-Ling Deng

    (Tsinghua University
    Hefei National Laboratory
    Shanghai Qi Zhi Institute)

  • Luyan Sun

    (Tsinghua University
    Hefei National Laboratory)

Abstract

Deep learning and quantum computing have achieved dramatic progresses in recent years. The interplay between these two fast-growing fields gives rise to a new research frontier of quantum machine learning. In this work, we report an experimental demonstration of training deep quantum neural networks via the backpropagation algorithm with a six-qubit programmable superconducting processor. We experimentally perform the forward process of the backpropagation algorithm and classically simulate the backward process. In particular, we show that three-layer deep quantum neural networks can be trained efficiently to learn two-qubit quantum channels with a mean fidelity up to 96.0% and the ground state energy of molecular hydrogen with an accuracy up to 93.3% compared to the theoretical value. In addition, six-layer deep quantum neural networks can be trained in a similar fashion to achieve a mean fidelity up to 94.8% for learning single-qubit quantum channels. Our experimental results indicate that the number of coherent qubits required to maintain does not scale with the depth of the deep quantum neural network, thus providing a valuable guide for quantum machine learning applications with both near-term and future quantum devices.

Suggested Citation

  • Xiaoxuan Pan & Zhide Lu & Weiting Wang & Ziyue Hua & Yifang Xu & Weikang Li & Weizhou Cai & Xuegang Li & Haiyan Wang & Yi-Pu Song & Chang-Ling Zou & Dong-Ling Deng & Luyan Sun, 2023. "Deep quantum neural networks on a superconducting processor," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39785-8
    DOI: 10.1038/s41467-023-39785-8
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