论文标题
Sycamore和Zuchongzhi量子处理器对随机量子抽样的统计分析
Statistical Analysis on Random Quantum Sampling by Sycamore and Zuchongzhi Quantum Processors
论文作者
论文摘要
随机量子采样的随机量子采样是从随机量子电路中采样比特串的任务，被认为是合适的基准任务之一，即使使用嘈杂的Qubits，也可以证明量子计算机的表现超越。最近，在使用53个Quarbits [Nature 574，505（2019）]和Zuchongzhi量子处理器的nicamore量子处理器上进行随机量子采样器，使用56量列表[Phys。莱特牧师。 127，180501（2021）]。在这里，我们分析和比较了Sycamore和Zuchongzhi的随机量子采样输出的统计特性。使用Marchenko-Pastur定律和Wassersertein距离，我们发现Zuchongzhi的量子随机采样比Sycamore更接近经典的均匀随机采样。一些Zuchongzhi的位弦通过了随机数测试，而Sycamore和Zuchongzhi都在比特弦的热图中显示出相似的模式。结果表明，随着随机量子电路的深度增加，两个随机量子样品的统计特性几乎没有变化。我们的发现提出了一个关于嘈杂量子处理器的计算可靠性的疑问，该计算可靠性可能会为相同的随机量子抽样任务产生统计上不同的输出。
Random quantum sampling, a task to sample bit-strings from a random quantum circuit, is considered one of suitable benchmark tasks to demonstrate the outperformance of quantum computers even with noisy qubits. Recently, random quantum sampling was performed on the Sycamore quantum processor with 53 qubits [Nature 574, 505 (2019)] and on the Zuchongzhi quantum processor with 56 qubits [Phys. Rev. Lett. 127, 180501 (2021)]. Here, we analyze and compare statistical properties of the outputs of random quantum sampling by Sycamore and Zuchongzhi. Using the Marchenko-Pastur law and the Wasssertein distances, we find that quantum random sampling of Zuchongzhi is more closer to classical uniform random sampling than those of Sycamore. Some Zuchongzhi's bit-strings pass the random number tests while both Sycamore and Zuchongzhi show similar patterns in heatmaps of bit-strings. It is shown that statistical properties of both random quantum samples change little as the depth of random quantum circuits increases. Our findings raise a question about computational reliability of noisy quantum processors that could produce statistically different outputs for the same random quantum sampling task.
