Author

Leonardo Ignazio Pagliochini

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#machine learning Preprint Oct 2026

Reducing the Cost of Qudit State Preparation by Learning a Sparse Structure for SNAP Gates

Preparing quantum states in bosonic qudits with SNAP--Displacement sequences requires both optimizing the gate parameters and deciding which Fock levels should be controlled by each SNAP gate. A fully parameterized ansatz assigns an independent phase to every Fock level in every gate, leading to a number of phases that...

M. Pennazio, Leonardo Ignazio Pagliochini, Riccardo Pellini et al. · 0 citations