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arXiv · 2207.06614

Demonstration of a bosonic quantum classifier with data re-uploading

Takafumi Ono·Wojciech Roga·Kentaro Wakui·Mikio Fujiwara·Shigehito Miki·Hirotaka Terai·Masahiro Takeoka
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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.

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Takafumi Ono, Wojciech Roga, Kentaro Wakui, Mikio Fujiwara, Shigehito Miki, Hirotaka Terai, Masahiro Takeoka. 2022-07-14. Demonstration of a bosonic quantum classifier with data re-uploading. https://doi.org/10.1103/physrevlett.131.013601

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