Deng Yu-Hao, Gu Yi-Chao, Liu Hua-Liang, Gong Si-Qiu, Su Hao, Zhang Zhi-Jiong, Tang Hao-Yang, Jia Meng-Hao, Xu Jia-Min, Chen Ming-Cheng, Qin Jian, Peng Li-Chao, Yan Jiarong, Hu Yi, Huang Jia, Li Hao, Li Yuxuan, Chen Yaojian, Jiang Xiao, Gan Lin, Yang Guangwen, You Lixing, Li Li, Zhong Han-Sen, Wang Hui, Liu Nai-Le, Renema Jelmer J, Lu Chao-Yang, Pan Jian-Wei
Hefei National Laboratory for Physical Sciences at Microscale and School of Physical Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China.
CAS Centre for Excellence and Synergetic Innovation Centre in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai 201315, China.
Phys Rev Lett. 2023 Oct 13;131(15):150601. doi: 10.1103/PhysRevLett.131.150601.
We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for the characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical spoofing mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ∼600 yr using exact methods, whereas our quantum computer, Jiǔzhāng 3.0, takes only 1.27 μs to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier∼3.1×10^{10} yr.
我们报告了采用伪光子数分辨检测的新型高斯玻色子采样实验，该实验记录了多达255个光子点击事件。我们考虑了部分光子可区分性，并开发了一个更完整的模型来表征有噪声的高斯玻色子采样。在量子计算优势领域，我们使用贝叶斯测试和相关函数分析，针对所有当前的经典欺骗模型来验证样本。用迄今为止最好的经典算法估计，在超级计算机“前沿”上使用精确方法从相同分布生成一个理想样本大约需要600年，而我们的量子计算机“九章3.0”生成一个样本仅需1.27微秒。使用精确算法从实验中生成最难的样本，“前沿”大约需要3.1×10^{10}年。
