We study the problem of learning a $ k $-body Hamiltonian with $ M $ unknown Pauli terms
that are not necessarily geometrically local. We propose a protocol that learns the …

Abstract Models for open quantum systems, which play important roles in electron transport
problems and quantum computing, must take into account the interaction of the quantum …

We study the problem of learning an unknown quantum many-body Hamiltonian $ H $ from
black-box queries to its time evolution $ e^{-\mathrm {i} H t} $. Prior proposals for solving this …

We initiate the study of Hamiltonian structure learning from real-time evolution: given the
ability to apply $ e^{-\mathrm {i} Ht} $ for an unknown local Hamiltonian $ H=\sum_ {a= 1} …

Recent work of three of the authors showed that the operator which maps the local density of
states of a one-dimensional untwisted bilayer material to the local density of states of the …

Abstract Quantum Graph Neural Networks (QGNN) are a new class of quantum neural
network ansatz which are tailored to represent quantum processes which have a graph …