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Training deep quantum neural networks
- Source :
- Nature Communications, Vol 11, Iss 1, Pp 1-6 (2020)
- Publication Year :
- 2020
- Publisher :
- Nature Portfolio, 2020.
-
Abstract
- 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 layers.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9ba2b872323438c9255d08c30daee30
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-020-14454-2