4 papers
Efficient learning of bosonic Gaussian unitaries
Marco Fanizza, Vishnu Iyer, Junseo Lee +2
Bosonic Gaussian unitaries are fundamental building blocks of central continuous-variable quantum technologies such as quantum-optic interferometry and bosonic error-correction sch…
Efficient Hamiltonian, structure and trace distance learning of Gaussian states
Marco Fanizza, Cambyse Rouzé, Daniel Stilck França
In this work, we initiate the study of Hamiltonian learning for positive temperature bosonic Gaussian states, the quantum generalization of the widely studied problem of learning G…
The NPA hierarchy does not always attain the commuting operator value
Marco Fanizza, Larissa Kroell, Arthur Mehta +4
We show that it is undecidable to determine whether the commuting operator value of a nonlocal game is strictly greater than 1/2. Specifically, there is a computable mapping from T…
Learning finitely correlated states: stability of the spectral reconstruction
Marco Fanizza, Niklas Galke, Josep Lumbreras +2
Matrix product operators allow efficient descriptions (or realizations) of states on a 1D lattice. We consider the task of learning a realization of minimal dimension from copies o…