Cited by 206Quantum Information and CryptographyQuantum Mechanics and ApplicationsQuantum Computing Algorithms and Architecture

Self-Testing Quantum Random Number Generator

Open access
Lunghi, Tommaso, Brask, Jonatan Bohr, Lim, Charles Ci Wen, Lavigne, Quentin, Bowles, Joseph, Martin, Anthony, Zbinden, Hugo, Brunner, Nicolas·2015·Physical Review Letters

Abstract

The generation of random numbers is a task of paramount importance in modern science. A central problem for both classical and quantum randomness generation is to estimate the entropy of the data generated by a given device. Here we present a protocol for self-testing quantum random number generation, in which the user can monitor the entropy in real time. Based on a few general assumptions, our protocol guarantees continuous generation of high quality randomness, without the need for a detailed characterization of the devices. Using a fully optical setup, we implement our protocol and illustrate its self-testing capacity. Our work thus provides a practical approach to quantum randomness generation in a scenario of trusted but error-prone devices.

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Crossref · 10.1103/physrevlett.114.150501

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  • The source and measurement devices can be assumed to occupy independent two-dimensional quantum subspaces.

    “For example, the source and measurement devices can be assumed to occupy independent two-dimensional quantum subspaces. 85”

    From Quantum random number generation (2016) · cites this paper as [85]

    The assumptions listed in “A self-testing quantum random number generator” (p. 3) treat the preparation and measurement devices as independent and restrict the information retrieved by the measurement device to a two-dimensional quantum subspace. They do not say that each device occupies its own independent two-dimensional quantum subspace. (LLM, conf=0.88)

    Experimental — accuracy not yet measured
  • There are QRNGs that achieve self-testing except under some mild assumptions.

    “Apart from the above two types of QRNGs, there are also some other QRNGs that achieve self-testing except under some mild assumptions.”

    From Quantum random number generation (2016) · cites this paper as [85]

    The paper presents and implements a self-testing QRNG based on a few general assumptions (p. 1). But it says that two of its assumptions are stronger and must be justified for each implementation (p. 3), so describing the assumptions collectively as mild overstates the source. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 3

  1. [12]T. Symul, S. M. Assad, and P. K. Lam, Applied Physics Letters 98 , 231103 (2011).
  2. [27]C. H. Bennett and G. Brassard, Proceedings of the IEEE International Conference on Computers, Systems and Signal Processing, Bangalore, India,175 (1984).
  3. [30]E. Wooten, K. Kissa, A. Yi-Yan, E. Murphy, D. Lafaw, P. Hallemeier, D. Maack, D. Attanasio, D. Fritz, G. McBrien, and D. Bossi, Sel. Topics in Quantum Electr., IEEE Journal of 6 , 69 (2000).

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Authors
Lunghi, T., Brask, J. B., Lim, C. C. W., Lavigne, Q., Bowles, J., Martin, A., Zbinden, H., & Brunner, N.
Affiliations
University of Geneva (CH)
Venue
Physical Review Letters
Published
2015-04-15
Volume
114
Issue
15
Pages
150501-150501
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
OpenAlex
W2025267340
Cited by
206
References
32
Citations by year
2026: 14 · 2025: 19 · 2024: 12 · 2023: 18 · 2022: 16 · 2021: 23 · 2020: 26 · 2019: 26 · 2018: 16 · 2017: 13 · 2016: 13 · 2015: 8 · 2014: 2
FWCI
16.31
Type
journal article
Language
en
Open access
Locations
  • Physical Review Letters (publishedVersion)
  • PubMed (publishedVersion)
  • Archive ouverte UNIGE (University of Geneva) (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • HAL (submittedVersion)
  • Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
  • arXiv (Cornell University)
Funders
  • Schweizerische Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PP00P2_138917, QSIT)
  • SEFRI
  • SIQS
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Mechanics and Applications
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
Keywords
quantum random number generation, self-testing, device-independent randomness

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