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- W4285597967 abstract "In a single qubit system, a universal quantum classifier can be realised using the data-reuploading technique. In this study, we propose a new quantum classifier applying this technique to bosonic systems and successfully demonstrated it using silicon optical integrated quantum circuits. We established a theory of quantum machine learning algorithm applicable to bosonic systems and implemented a programmable optical circuit combined with an interferometer. Learning and classification using part of the implemented optical quantum circuit with uncorrelated two-photons resulted in a classification with a reproduction rate of approximately 94% in the proof of principle experiment. As this method can be applied to arbitrary two-mod N-photon system, further development of optical quantum classifiers, such as extensions to quantum entangled and multi-photon states, is expected in the future." @default.
- W4285597967 created "2022-07-16" @default.
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- W4285597967 date "2022-07-13" @default.
- W4285597967 modified "2023-09-27" @default.
- W4285597967 title "Demonstration of a bosonic quantum classifier with data re-uploading" @default.
- W4285597967 doi "https://doi.org/10.48550/arxiv.2207.06614" @default.
- W4285597967 hasPublicationYear "2022" @default.
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