Training deep quantum neural networks

It is hard to design quantum neural networks able to work with quantum data. Here, the authors propose a noise-robust architecture for a feedforward quantum neural network, with qudits as neurons and arbitrary unitary operations as perceptrons, whose training procedure is efficient in the number of...

Full description

Bibliographic Details
Main Authors: Kerstin Beer, Dmytro Bondarenko, Terry Farrelly, Tobias J. Osborne, Robert Salzmann, Daniel Scheiermann, Ramona Wolf
Format: Article
Language:English
Published: Nature Portfolio 2020-02-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-020-14454-2