Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/9CB079A3-6AEB-49C4-8B09-FA578377E764 | ||
| Year | 2021 | ||
| Type of Item | Conference Short Paper | ||
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| Bibliographic Citation | G. B. Yee, D. Leykam and D. G. Angelakis, "Fock state-enhanced expressivity of quantum machine learning models," presented at the 2021 Conference on Lasers and Electro-Optics (CLEO), San Jose, CA, USA, 2021. | ||
| Appears in Collections |
We propose quantum classifiers based on encoding classical data onto Fock states using tunable beam-splitter meshes, similar to the boson sampling architecture. We show that higher photon numbers enhance the expressive power of the circuit.
Copyright © DIAS 2013
