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arXiv:2404.15603 · Quantum Information Processing

Extension of a pattern recognition validation approach for noisy boson sampling

Ji Yang, Yongzheng Wu, Shi Wang, Jie Shan Hou, Meiling Chen, Ming Ni

Published Mar 17, 2025• 0 citations
arXivHTMLPDF
DOI
10.1007/s11128-025-04705-w

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Gaussian boson sampling (GBS) is a variety of boson sampling overcoming the stable single-photon preparation difficulty of the later. However, like those in the original version, noises in GBS will also result in the deviation of output patterns and the reduction of classical simulation complexity. We extend the pattern recognition validation, together with the correlation approach as a comparison, on GBS using photon number resolving detectors, with noises of both photon loss and distinguishability, to quantificationally evaluate noise levels. As for the classical simulation with noises to be used during validations, it is actually a simulation of mixed states where we employ an existing photon-pair strategy to realize polynomial speedup locally. Furthermore, we use an output-binning strategy to realize validation speedup. Our simulation indicates that the pattern recognition protocol is useful for noise evaluations of GBS even when noises are sufficiently low.