Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases

Herrmann J, Llima SM, Remm A, Zapletal P, McMahon N, Scarato C, Swiadek F, Andersen CK, Hellings C, Krinner S, Lacroix N, Lazar S, Kerschbaum M, Zanuz DC, Norris GJ, Hartmann M, Wallraff A, Eichler C (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Nature Communications Nature Publishing Group: Nature Communications

Book Volume: 13

Journal Issue: 1

DOI: 10.1038/s41467-022-31679-5

Abstract

Quantum neural networks could help analysing the output of quantum computers and quantum simulators of growing complexity. Here, the authors use a 7-qubit superconducting quantum processor to show how a quantum convolutional neural network can correctly recognise the phase of a quantum many-body state.

Authors with CRIS profile

Petr Zapletal Lehrstuhl für Theoretische Physik Nathan McMahon Lehrstuhl für Theoretische Physik Michael Hartmann Lehrstuhl für Theoretische Physik Christopher Eichler

Involved external institutions

Eidgenössische Technische Hochschule Zürich (ETHZ) / Swiss Federal Institute of Technology in Zurich CH Switzerland (CH)

How to cite

APA:

Herrmann, J., Llima, S.M., Remm, A., Zapletal, P., McMahon, N., Scarato, C.,... Eichler, C. (2022). Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases. Nature Communications, 13(1). https://dx.doi.org/10.1038/s41467-022-31679-5

MLA:

Herrmann, Johannes, et al. "Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases." Nature Communications 13.1 (2022).

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