Gaussian Boson Sampling with Pseudo-Photon-Number-Resolving Detectors and Quantum Computational Advantage

Yu Hao Deng, Yi Chao Gu, Hua Liang Liu, Si Qiu Gong, Hao Su, Zhi Jiong Zhang, Hao Yang Tang, Meng Hao Jia, Jia Min Xu, Ming Cheng Chen, Jian Qin, Li Chao Peng, Jiarong Yan, Yi Hu, Jia Huang, Hao Li, Yuxuan Li, Yaojian Chen, Xiao Jiang, Lin GanGuangwen Yang, Lixing You, Li Li, Han Sen Zhong, Hui Wang, Nai Le Liu, Jelmer J. Renema, Chao Yang Lu, Jian Wei Pan

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

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, Jizhāng 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∼3.1×1010 yr.

Original languageEnglish
Article number150601
JournalPhysical review letters
Volume131
Issue number15
DOIs
Publication statusPublished - 13 Oct 2023

Keywords

  • 2024 OA procedure

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