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量子生成对抗网络抗噪优化的容错量子隐形传态系统
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作者 李嘉鑫 史尚尚 +3 位作者 尚瑞敏 李亚男 王志敏 顾永建 《中国科学:信息科学》 CSCD 北大核心 2024年第6期1541-1557,共17页
量子生成对抗网络(quantum generative adversarial networks,QGAN)在图像处理、金融分析等领域应用中展现出了优越的性能.本文首次提出了一种基于量子生成对抗网络的量子拓扑码解码器,并应用于优化容错量子隐形传态系统.在本文中,首先... 量子生成对抗网络(quantum generative adversarial networks,QGAN)在图像处理、金融分析等领域应用中展现出了优越的性能.本文首次提出了一种基于量子生成对抗网络的量子拓扑码解码器,并应用于优化容错量子隐形传态系统.在本文中,首先构建并测试了QGAN算法的量子线路,搭建了拓扑码解码器训练模型.其次,针对拓扑码本征值数据集,设计了算法的输入输出,并训练得到高效率的解码模型.最后,构建了带有QGAN解码器的拓扑码优化量子隐形传态系统,相较于原始系统展现出更好的容错性能.在码距d=3及d=5的解码实验表明,本模型纠错成功率可以达到99.887%.在实验中,本QGAN解码器的保真度阈值约为P=0.1706,相较经典解码模型阈值约为P=0.1099,有了明显提升.另外,量子隐形传态系统在d=3拓扑码优化抗噪下,在非极化噪声阈值P<0.0607范围内具有明显的保真度提升;在d=5拓扑码优化抗噪下,在非极化噪声阈值P<0.0778范围内具有明显的保真度提升.本文提出的QGAN解码模型,结合了量子隐形传态方法,为量子深度学习的应用提供了新思路,并可应用于其他非均匀噪声处理领域. 展开更多
关键词 量子生成对抗网络 拓扑码 解码器 非极化噪声 量子隐形传态 保真度
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Algorithm for simulating ocean circulation on a quantum computer
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作者 ruimin shang Zhimin WANG +3 位作者 shangshang SHI Jiaxin LI Yanan LI Yongjian GU 《Science China Earth Sciences》 SCIE EI CAS CSCD 2023年第10期2254-2264,共11页
The accurate and efficient simulation of ocean circulation is a fundamental topic in marine science;however,it is also a well-known and dauntingly difficult problem that requires solving nonlinear partial differential... The accurate and efficient simulation of ocean circulation is a fundamental topic in marine science;however,it is also a well-known and dauntingly difficult problem that requires solving nonlinear partial differential equations with multiple variables.In this paper,we present for the first time an algorithm for simulating ocean circulation on a quantum computer to achieve a computational speedup.Our approach begins with using primitive equations describing the ocean dynamics and then discretizing these equations in time and space.It results in several linear system of equations(LSE)with sparse coefficient matrices.We solve these sparse LSE using the variational quantum linear solver that enables the present algorithm to run easily on near-term quantum computers.Additionally,we develop a scheme for manipulating the data flow in the algorithm based on the quantum random access memory and l∞norm tomography technique.The efficiency of our algorithm is verified using multiple platforms,including MATLAB,a quantum virtual simulator,and a real quantum computer.The impact of the number of shots and the noise of quantum gates on the solution accuracy is also discussed.Our findings demonstrate that error mitigation techniques can efficiently improve the solution accuracy.With the rapid advancements in quantum computing,this work represents an important first step toward solving the challenging problem of simulating ocean circulation using quantum computers. 展开更多
关键词 Ocean circulation Primitive equations Linear system of equations Variational quantum linear solver Error mitigation technique
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