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Paper 2020/078

Quantum Random Number Generation with the Superconducting Quantum Computer IBM 20Q Tokyo

Kentaro Tamura and Yutaka Shikano

Abstract

Quantum random number generators (QRNGs) produce theoretically unpredictable random numbers. A typical QRNG is implemented in quantum optics [Herrero-Collantes, M., Garcia-Escartin, J. C.: Quantum Random Number Generators. Rev. Mod. Phys. \textbf{89}, 015004 (2017)]. Quantum computers become QRNGs when given certain programs. The simplest example of such a program applies the Hadamard gate on all qubits and performs measurement. As a result of repeatedly running this program on a 20-qubit superconducting quantum computer (IBM 20Q Tokyo), we obtained a sample with a length of 43,560. However, statistical analysis showed that this sample was biased and correlated. One of the post-processed samples passed statistical tests. To show the effectiveness of post-processing, a larger sample size is required. The present study of quantum random number generation and statistical testing may provide a potential candidate for benchmarking tests of actual quantum computing devices.

Note: Published version of Proceedings of Workshop on Quantum Computing and Quantum Information edited by Mika Hirvensalo and Abuzer Yakaryilmaz held on June 7th, 2019 at Fuchu, Tokyo.

Metadata
Available format(s)
PDF
Category
Foundations
Publication info
Published elsewhere. TUCS Lecture Notes 30, 13 - 25 (2019)
Keywords
pseudo-randomnessquantum random number generator
Contact author(s)
cicero @ keio jp
yutaka shikano @ keio jp
History
2020-01-26: revised
2020-01-26: received
See all versions
Short URL
https://ia.cr/2020/078
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2020/078,
      author = {Kentaro Tamura and Yutaka Shikano},
      title = {Quantum Random Number Generation with the Superconducting Quantum Computer IBM 20Q Tokyo},
      howpublished = {Cryptology ePrint Archive, Paper 2020/078},
      year = {2020},
      note = {\url{https://eprint.iacr.org/2020/078}},
      url = {https://eprint.iacr.org/2020/078}
}
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