Effects of Quantum Noise on Quantum Approximate Optimization Algorithm
Effects of Quantum Noise on Quantum Approximate Optimization Algorithm
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DOI：
10.1088/0256-307x/38/3/030302
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发表时间：
2021-03-01
影响因子：
3.5
通讯作者：
Guo, Guo-Ping
中科院分区：
文献类型：
--
作者：
Xue, Cheng;Chen, Zhao-Yun;Guo, Guo-Ping
量子-经典混合算法是在噪声-中尺度量子（NISQ）器件中展示量子优势的一种很有前途的算法。在运行这种算法时，量子噪声的影响是不可避免的。在我们的工作中，我们考虑了一个众所周知的混合算法，量子近似优化算法（QAOA）。研究了典型的量子噪声通道对QAOA的影响，并给出了一些数值结果。我们的研究表明，输出状态保真度，即从QAOA获得的成本函数，相对于门的数量和噪声强度呈指数下降。此外，我们发现当噪声不严重时，优化后的参数不会偏离理想值。我们的结果为在NISQ设备上运行混合算法的有效性提供了证据。
The quantum-classical hybrid algorithm is a promising algorithm with respect to demonstrating the quantum advantage in noisy-intermediate-scale quantum (NISQ) devices. When running such algorithms, effects due to quantum noise are inevitable. In our work, we consider a well-known hybrid algorithm, the quantum approximate optimization algorithm (QAOA). We study the effects on QAOA from typical quantum noise channels, and produce several numerical results. Our research indicates that the output state fidelity, i.e., the cost function obtained from QAOA, decreases exponentially with respect to the number of gates and noise strength. Moreover, we find that when noise is not serious, the optimized parameters will not deviate from their ideal values. Our result provides evidence for the effectiveness of hybrid algorithms running on NISQ devices.