Quantum generative adversarial networks based on a readout error mitigation method with fault tolerant mechanism

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外文摘要：Readout errors caused by measurement noise are a significant source of errors in quantum circuits,which severely affect the output results and are an urgent problem to be solved in noisy-intermediate scale quantum(NISQ)computing.In this paper,we use the bit-flip averaging(BFA)method to mitigate frequent readout errors in quantum generative adversarial networks(QGAN)for image generation,which simplifies the response matrix structure by averaging the qubits for each random bit-flip in advance,successfully solving problems with high cost of measurement for traditional error mitigation methods.Our experiments were simulated in Qiskit using the handwritten digit image recognition dataset under the BFA-based method,the Kullback-Leibler(KL)divergence of the generated images converges to 0.04,0.05,and 0.1 for readout error probabilities of p=0.01,p=0.05,and p=0.1,respectively.Additionally,by evaluating the fidelity of the quan-tum states representing the images,we observe average fidelity values of 0.97,0.96,and 0.95 for the three readout error probabilities,respectively.These results demonstrate the robustness of the model in mitigating readout errors and provide a highly fault tolerant mechanism for image generation models.

外文关键词：

readout errorsquantum generative adversarial networksbit-flip averaging methodfault tolerant mechanisms

作者：

赵润盛、马鸿洋、程涛、王爽、范兴奎

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作者单位：

School of Sciences,Qingdao University of Technology,Qingdao 266033,China

School of Information and Control Engineering,Qingdao University of Technology,Qingdao 266033,China

基金：

山东省自然科学基金Joint Fund of Natural Science Foundation of Shandong ProvinceJoint Fund of Natural Science Foundation of Shandong Province

项目编号：

ZR2021MF049ZR2022LLZ012ZR2021LLZ001

出版年：

2024

DOI：

10.1088/1674-1056/ad02e7

中国物理B(英文版)

中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI

影响因子：0.995

ISSN：1674-1056

年,卷(期)：2024.33(4)

参考文献量62