Variational quantum circuits for quantum state tomography
Variational quantum circuits for quantum state tomography
复制标题
用于量子态断层扫描的变分量子电路
DOI：
10.1103/physreva.101.052316
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发表时间：
2020-05-11
影响因子：
2.9
通讯作者：
Wu, Junjie
中科院分区：
文献类型：
--
作者：
Liu, Yong;Wang, Dongyang;Wu, Junjie
量子态层析成像是大多数量子实验的关键过程。在这项工作中，我们将量子机器学习用于状态断层扫描。给定一个未知的量子态，它可以通过最大化变分量子电路输出与该状态之间的保真度来学习。变分量子电路的参数数量随量子比特数和电路深度线性增长，因此即使对于高度纠缠态，也只需要多项式测量。然后，利用随后的经典电路模拟器将变分量子电路中的目标量子态信息转换为熟悉的格式。我们通过使用变分量子电路模拟器对一维量子自旋链基态的层析成像进行数值模拟来证明我们的方法。该方法适用于近期量子计算平台，可用于实验相关量子态的相对大规模量子态断层扫描。
Quantum state tomography is a key process in most quantum experiments. In this work, we employ quantum machine learning for state tomography. Given an unknown quantum state, it can be learned by maximizing the fidelity between the output of a variational quantum circuit and this state. The number of parameters of the variational quantum circuit grows linearly with the number of qubits and the circuit depth, so that only polynomial measurements are required, even for highly entangled states. After that, a subsequent classical circuit simulator is used to transform the information of the target quantum state from the variational quantum circuit into a familiar format. We demonstrate our method by performing numerical simulations for the tomography of the ground state of a one-dimensional quantum spin chain, using a variational quantum circuit simulator. Our method is suitable for near-term quantum computing platforms, and could be used for relatively large-scale quantum state tomography for experimentally relevant quantum states.