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.
@article{arxiv.1106.4254,
title = {Dynamic learning of pairwise and three-way entanglement},
author = {Elizabeth Behrman and James Steck},
journal= {arXiv preprint arXiv:1106.4254},
year = {2011}
}
Comments
6 pages; 2 figures; 5 tables; Submitted to NaBIC 2011