Fock State-enhanced Expressivity of Quantum Machine Learning Models

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.