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Boson Sampling with Gaussian input states: toward efficient scaling and certification

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arxiv 1812.08978 v6 pith:WLWYGBSF submitted 2018-12-21 quant-ph

classification quant-ph
keywords bosonsamplingquantumcomputationalscaleadvantagecertificationcombination
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A universal quantum computer of large scale is not available yet, however, intermediate models of quantum computation would still permit demonstrations of a quantum computational advantage over classical computing and could challenge the Extended Church-Turing Thesis. One of these models based on single photons interacting via linear optics is called Boson Sampling. Although Boson Sampling was demonstrated and the threshold to claim quantum computational advantage was achieved, the question of how to scale up Boson Sampling experiments remains. To make progress with this problem, here we present a practically achievable pathway to scale Boson Sampling experiments by combining continuous-variable quantum information and temporal encoding. We propose the combination of switchable dual-homodyne and single-photon detections, the temporal loop technique, and scattershot-based Boson Sampling. We detail the required assumptions for concluding computational hardness for this configuration. Furthermore, this particular combination of techniques moves towards an efficient scaling and certification of Boson Sampling, all in a single experimental setup.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. In situ characterization of linear-optical networks in randomized boson sampling

    quant-ph 2019-09 accept novelty 7.0 of 10

    A distributed protocol lets one party characterize a lossy linear-optical network during randomized boson sampling by using heterodyne measurements on shared squeezed light, with effort that grows linearly in the numb...

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