Pan Feng, Chen Keyang, Zhang Pan
CAS Key Laboratory for Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China.
School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
Phys Rev Lett. 2022 Aug 26;129(9):090502. doi: 10.1103/PhysRevLett.129.090502.
We study the problem of generating independent samples from the output distribution of Google's Sycamore quantum circuits with a target fidelity, which is believed to be beyond the reach of classical supercomputers and has been used to demonstrate quantum supremacy. We propose a method to classically solve this problem by contracting the corresponding tensor network just once, and is massively more efficient than existing methods in generating a large number of uncorrelated samples with a target fidelity. For the Sycamore quantum supremacy circuit with 53 qubits and 20 cycles, we have generated 1×10^{6} uncorrelated bitstrings s which are sampled from a distribution Pover ^=|ψover ^|^{2}, where the approximate state ψ[over ^] has fidelity F≈0.0037. The whole computation has cost about 15 h on a computational cluster with 512 GPUs. The obtained 1×10^{6} samples, the contraction code and contraction order are made public. If our algorithm could be implemented with high efficiency on a modern supercomputer with ExaFLOPS performance, we estimate that ideally, the simulation would cost a few dozens of seconds, which is faster than Google's quantum hardware.
我们研究了从谷歌的Sycamore量子电路输出分布中生成具有目标保真度的独立样本的问题,该保真度被认为超出了经典超级计算机的能力范围,并且已被用于证明量子优越性。我们提出了一种通过仅一次收缩相应的张量网络来经典地解决此问题的方法,该方法在生成大量具有目标保真度的不相关样本方面比现有方法效率大幅提高。对于具有53个量子比特和20个周期的Sycamore量子优越性电路,我们已经生成了1×10⁶个不相关的比特串s,它们是从分布P̂(s)=|ψ̂(s)|²中采样得到的,其中近似态ψ̂的保真度F≈0.0037。在具有512个GPU的计算集群上,整个计算花费了大约15小时。所获得的1×10⁶个样本、收缩代码和收缩顺序已公开。如果我们的算法能够在具有百亿亿次性能的现代超级计算机上高效实现,我们估计理想情况下,模拟将花费几十秒,这比谷歌的量子硬件还要快。