Trainability of Dissipative Perceptron-Based Quantum Neural Networks

Several architectures have been proposed for quantum neural networks (QNNs), with the goal of efficiently performing machine learning tasks on quantum data. Rigorous scaling results are urgently needed for specific QNN constructions to understand which, if any, will be trainable at a large scale. He...

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Bibliographic Details

Published in:	Physical review letters Vol. 128; no. 18; p. 180505
Main Authors:	Sharma, Kunal, Cerezo, M., Cincio, Lukasz, Coles, Patrick J.
Format:	Journal Article
Language:	English
Published:	United States American Physical Society (APS) 06.05.2022
Subjects:	artificial neural networks CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS machine learning quantum algorithms quantum computation quantum information processing quantum networks
ISSN:	0031-9007, 1079-7114, 1079-7114
Online Access:	Get full text
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