Marco Fanizza

Efficient Hamiltonian, structure and trace distance learning of Gaussian states

Abstract When learning descriptions of many-body quantum systems, assuming locality of interactions can dramatically reduce the required number of observations and computational time compared to unstructured approaches. In this work, we uncover an infinite-dimensional instance of...