Demonstration of a bosonic quantum classifier with data re-uploading
- URL: http://arxiv.org/abs/2207.06614v1
- Date: Thu, 14 Jul 2022 02:05:55 GMT
- Title: Demonstration of a bosonic quantum classifier with data re-uploading
- Authors: Takafumi Ono, Wojciech Roga, Kentaro Wakui, Mikio Fujiwara, Shigehito
Miki, Hirotaka Terai, Masahiro Takeoka
- Abstract summary: In a single qubit system, a universal quantum classifier can be realised using the data-reuploading technique.
We propose a new quantum classifier applying this technique to bosonic systems and successfully demonstrated it using silicon optical integrated quantum circuits.
- Score: 0.1616312990391151
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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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