Supervised quantum gate "teaching" for quantum hardware design
Machine Learning
2016-07-22 v1 Quantum Physics
Machine Learning
Abstract
We show how to train a quantum network of pairwise interacting qubits such that its evolution implements a target quantum algorithm into a given network subset. Our strategy is inspired by supervised learning and is designed to help the physical construction of a quantum computer which operates with minimal external classical control.
Cite
@article{arxiv.1607.06146,
title = {Supervised quantum gate "teaching" for quantum hardware design},
author = {Leonardo Banchi and Nicola Pancotti and Sougato Bose},
journal= {arXiv preprint arXiv:1607.06146},
year = {2016}
}
Comments
6 pages, 1 figure, based on arXiv:1509.04298