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Continuous-variable quantum computing on encrypted data

Author

Listed:
  • Kevin Marshall

    (University of Toronto)

  • Christian S. Jacobsen

    (Technical University of Denmark)

  • Clemens Schäfermeier

    (Technical University of Denmark)

  • Tobias Gehring

    (Technical University of Denmark)

  • Christian Weedbrook

    (CipherQ)

  • Ulrik L. Andersen

    (Technical University of Denmark)

Abstract

The ability to perform computations on encrypted data is a powerful tool for protecting a client’s privacy, especially in today’s era of cloud and distributed computing. In terms of privacy, the best solutions that classical techniques can achieve are unfortunately not unconditionally secure in the sense that they are dependent on a hacker’s computational power. Here we theoretically investigate, and experimentally demonstrate with Gaussian displacement and squeezing operations, a quantum solution that achieves the security of a user’s privacy using the practical technology of continuous variables. We demonstrate losses of up to 10 km both ways between the client and the server and show that security can still be achieved. Our approach offers a number of practical benefits (from a quantum perspective) that could one day allow the potential widespread adoption of this quantum technology in future cloud-based computing networks.

Suggested Citation

  • Kevin Marshall & Christian S. Jacobsen & Clemens Schäfermeier & Tobias Gehring & Christian Weedbrook & Ulrik L. Andersen, 2016. "Continuous-variable quantum computing on encrypted data," Nature Communications, Nature, vol. 7(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms13795
    DOI: 10.1038/ncomms13795
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    Cited by:

    1. Cheng, Zhen-Wen & Chen, Xiu-Bo & Xu, Gang & Ma, Li & Li, Zong-Peng, 2024. "Quantum one-time pad-based quantum homomorphic encryption schemes for circuits of the non-Clifford gates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    2. Beatrice Polacchi & Dominik Leichtle & Leonardo Limongi & Gonzalo Carvacho & Giorgio Milani & Nicolò Spagnolo & Marc Kaplan & Fabio Sciarrino & Elham Kashefi, 2023. "Multi-client distributed blind quantum computation with the Qline architecture," Nature Communications, Nature, vol. 14(1), pages 1-8, December.

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