Training deep quantum neural networks

Research output: Contribution to journal › Article › Research › peer review

Authors

  • Kerstin Beer
  • Dmytro Bondarenko
  • Terry Farrelly
  • Tobias J. Osborne
  • Robert Salzmann
  • Daniel Scheiermann
  • Ramona Wolf

Research Organisations

External Research Organisations

  • University of Queensland
  • University of Cambridge
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Details

Original languageEnglish
Article number808
Pages (from-to)808
JournalNature Communications
Volume11
Issue number1
Publication statusPublished - 10 Feb 2020

Abstract

Neural networks enjoy widespread success in both research and industry and, with the advent of quantum technology, it is a crucial challenge to design quantum neural networks for fully quantum learning tasks. Here we propose a truly quantum analogue of classical neurons, which form quantum feedforward neural networks capable of universal quantum computation. We describe the efficient training of these networks using the fidelity as a cost function, providing both classical and efficient quantum implementations. Our method allows for fast optimisation with reduced memory requirements: the number of qudits required scales with only the width, allowing deep-network optimisation. We benchmark our proposal for the quantum task of learning an unknown unitary and find remarkable generalisation behaviour and a striking robustness to noisy training data.

ASJC Scopus subject areas

Cite this

Training deep quantum neural networks. / Beer, Kerstin; Bondarenko, Dmytro; Farrelly, Terry et al.
In: Nature Communications, Vol. 11, No. 1, 808, 10.02.2020, p. 808.

Research output: Contribution to journal › Article › Research › peer review

Beer, K, Bondarenko, D, Farrelly, T, Osborne, TJ, Salzmann, R, Scheiermann, D & Wolf, R 2020, 'Training deep quantum neural networks', Nature Communications, vol. 11, no. 1, 808, pp. 808. https://doi.org/10.1038/s41467-020-14454-2, https://doi.org/10.15488/9906
Beer, K., Bondarenko, D., Farrelly, T., Osborne, T. J., Salzmann, R., Scheiermann, D., & Wolf, R. (2020). Training deep quantum neural networks. Nature Communications, 11(1), 808. Article 808. https://doi.org/10.1038/s41467-020-14454-2, https://doi.org/10.15488/9906
Beer K, Bondarenko D, Farrelly T, Osborne TJ, Salzmann R, Scheiermann D et al. Training deep quantum neural networks. Nature Communications. 2020 Feb 10;11(1):808. 808. doi: 10.1038/s41467-020-14454-2, 10.15488/9906
Beer, Kerstin ; Bondarenko, Dmytro ; Farrelly, Terry et al. / Training deep quantum neural networks. In: Nature Communications. 2020 ; Vol. 11, No. 1. pp. 808.
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