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Gaussian Boson Sampling with Pseudo-Photon-Number Resolving Detectors and Quantum Computational Advantage
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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 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 years using exact methods, whereas our quantum computer, Jiuzhang 3.0, takes only 1.27 us to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier ~ 3.1*10^10 years.
Forward citations
Cited by 2 Pith papers
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Experimental validation of boson sampling using detector binning
Binned-mode photon-count distributions validate three-photon boson sampling over 50 random interferometers, and their Haar-averaged variance is proportional to the sum of squared photon overlaps.
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Matrix product state approach to lossy boson sampling and noisy IQP sampling
Lossy boson sampling and noisy IQP sampling are classically simulable with matrix product states, with the same known noise thresholds and accuracy controlled by bond dimension.
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