# Fock state-enhanced expressivity of quantum machine learning models

@article{Gan2021FockSE, title={Fock state-enhanced expressivity of quantum machine learning models}, author={Beng Yee Gan and Daniel Leykam and D. G. Angelakis}, journal={EPJ Quantum Technology}, year={2021}, volume={9}, pages={1-23} }

The data-embedding process is one of the bottlenecks of quantum machine learning, potentially negating any quantum speedups. In light of this, more effective data-encoding strategies are necessary. We propose a photonic-based bosonic data-encoding scheme that embeds classical data points using fewer encoding layers and circumventing the need for nonlinear optical components by mapping the data points into the high-dimensional Fock space. The expressive power of the circuit can be controlled via…

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