Toward scalable boson sampling with photon loss
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Boson sampling is a well-defined task that is strongly believed to be intractable for classical computers, but can be efficiently solved by a specific quantum simulator. However, an outstanding problem for large-scale experimental boson sampling is the scalability. Here we report an experiment on boson sampling with photon loss, and demonstrate that boson sampling with a few photons lost can increase the sampling rate. Our experiment uses a quantum-dot-micropillar single-photon source demultiplexed into up to seven input ports of a 16×16 mode ultra-low-loss photonic circuit, and we detect three-, four- and five-fold coincidence counts. We implement and validate lossy boson sampling with one and two photons lost, and obtain sampling rates of 187 kHz, 13.6 kHz, and 0.78 kHz for five-, six- and seven-photon boson sampling with two photons lost, which is 9.4, 13.9, and 18.0 times faster than the standard boson sampling, respectively. Our experiment shows an approach to significantly enhance the sampling rate of multiphoton boson sampling.
Wang , H , Li , W , Jiang , X , He , Y -M , Li , Y -H , Ding , X , Chen , M -C , Qin , J , Peng , C -Z , Schneider , C , Kamp , M , Zhang , W -J , Li , H , You , L -X , Wang , Z , Dowling , J P , Höfling , S , Lu , C-Y & Pan , J-W 2018 , ' Toward scalable boson sampling with photon loss ' , Physical Review Letters , vol. 120 , no. 23 , 230502 . https://doi.org/10.1103/PhysRevLett.120.230502
Physical Review Letters
© 2018, American Physical Society. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1103/PhysRevLett.120.230502
DescriptionThis work was supported by the National Natural Science Foundation of China, the Chinese Academy of Science, the Science and Technology Commission of Shanghai Municipality, the National Fundamental Research Program, the State of Bavaria, and the US National Science Foundation.
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