  In previous work, we have developed a dynamic learning paradigm for
"programming" a general quantum computer. A learning algorithm is used to find
a set of parameters for a coupled qubit system such that the system at an
initial time evolves to a state in which a given measurement results in the
desired calculation value. This can be thought of as a quantum neural network
(QNN). Here, we apply our method to a system of three qubits, and demonstrate
training the quantum computer to estimate both pairwise and three-way
entanglement.
