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Quantum computational advantage using photons

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Science  18 Dec 2020:
Vol. 370, Issue 6523, pp. 1460-1463
DOI: 10.1126/science.abe8770

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  • Can quantum artificial intelligence be more explainable than classical artificial intelligence?
    • Yuichi Hirata, Associate Professor, Hokkaido University, Central Institute of Isotope Science, and Graduate School of Biomedical Science and Engineering

    The quantum computation which was reported in (1) may be used for quantum artificial intelligence.
    In the quantum artificial intelligence, information processing processes can be represented by combinations of quantum mechanical operators which can be explained by quantum mechanics.
    On the other hand, a mechanism of the information processing processes of classical artificial intelligence implemented in ordinary classical computers is generally inside a black box.
    Therefore, the quantum artificial intelligence may be able to be more explainable than the classical artificial intelligence.
    REFERENCES
    1. Han-Sen Zhong, et al., Quantum computational advantage using photons, Science, Vol. 370, Issue 6523, pp. 1460-1463 (2020).

    Competing Interests: None declared.
  • Will quantum computers match machine learning to overcome theoretical predictions?
    • Yuichi Hirata, Associate Professor, Hokkaido University, Central Institute of Isotope Science, and Graduate School of Biomedical Science and Engineering

    As reported in (1), the outputs of the quantum computation using photons reproduced the theoretical predictions.
    However, completely new outputs of the quantum computers which overcome the theoretical predictions shall be validated and verified.
    In order to validate and verify the completely new outputs of the quantum computers, inputs for the quantum computer shall firstly be validated and verified.
    For example, for such validation and verification, we shall ensure that the inputs for the quantum computer shall be based on mathematically exact analytical solutions.
    For example, the inputs for the quantum computers can be created by machine learning algorithms which use the mathematically exact analytical solutions as learning data.
    Such matching of the quantum computers and the machine learning algorithms may be able to become a basis to overcome the theoretical predictions.
    REFERENCES
    1. Han-Sen Zhong, et al., Quantum computational advantage using photons, Science, Vol. 370, Issue 6523, pp. 1460-1463 (2020).

    Competing Interests: None declared.
  • Will quantum computers overcome theoretical predictions?
    • Yuichi Hirata, Associate Professor, Hokkaido University, Central Institute of Isotope Science, and Graduate School of Biomedical Science and Engineering

    As reported in (1), the outputs of the quantum computation using photons were assumed to be true by the comparisons between the outputs and the theoretical predictions.
    However, if the theoretical predictions will be impossible in future use cases, we will not be able to perform such comparisons.
    Therefore, it will be serious problems to develop how to validate and verify the outputs of the quantum computers to ensure trustworthiness of the quantum computers.

    REFERENCES

    1. Han-Sen Zhong, et al., Quantum computational advantage using photons, Science, 03 Dec 2020, eabe8770 (2020).

    Competing Interests: None declared.

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