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.
@article{arxiv.2207.06614,
title = {Demonstration of a bosonic quantum classifier with data re-uploading},
author = {Takafumi Ono and Wojciech Roga and Kentaro Wakui and Mikio Fujiwara and Shigehito Miki and Hirotaka Terai and Masahiro Takeoka},
journal= {arXiv preprint arXiv:2207.06614},
year = {2023}
}