Implement quantum random number generation on the IBM quantum computer platform
Email:
quynhln@actvn.edu.vn
Từ khóa:
AIS-31, Hadamard gate, Measurement, NIST SP 800-22, QRNG, Qubit
Tóm tắt
Random numbers are a crucial component of any encryption activity in modern cryptography. Quantum Random Number Generators (QRNGs) produce truly random output strings to replace pseudo-random ones. The principle of QRNG relies on measuring qubit states, which excel in quantum computing applications, particularly on IBM's quantum computing platform. To construct a random number generator, the authors utilized IBM Q Experience's Qiskit quantum development toolkit. We developed QRNG applications on IBM quantum computers (7-qubit, 16-qubit, and 127-qubit) and tested the program's functionality on these quantum computing platforms. The quality assessment of the random strings was conducted according to NIST and AIS-31 standards. For NIST standards, to achieve good quality, the output string must reach a minimum of 1,593,088 bits to pass 16 tests per SP800-22 standard. According to AIS-31 standards, to achieve good quality, the output string must reach a minimum of 8,000,000 bits to pass 8 tests of the standardTài liệu tham khảo
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[25]. Y. Li et al., Analysis of the effects of temperature increase on quantum random number generator, The European Physical Journal D, 75 (2021) 69. https://doi.org/10.1140/epjd/s10053-021-00087-7.
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[27]. V. Mannalath, S. Mishra, A. Pathak, A Comprehensive Review of Quantum Random Number Generators: Concepts, Classification and the Origin of Randomness, 22 (2023) 439. http://arxiv.org/abs/2203.00261
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[2]. J. Sen Teh, W. Teng, A. Samsudin, J. Chen, A post-processing method for true random number generators based on hyperchaos with applications in audio-based generators, Frontiers of Computer Science, 14 (2020) 146405. https://doi.org/10.1007/s11704-019-9120-2.
[3]. L. Deng, D. Bowman, Developments in pseudo‐random number generators, WIREs Computational Statistics, 9 (2017) 1404. https://doi.org/10.1002/wics.1404.
[4]. A. Shukla et al., A True Random Number Generator for Probabilistic Computing using Stochastic Magnetic Actuated Random Transducer Devices, in 2023 24th International Symposium on Quality Electronic Design (ISQED), (2023) 1–10. https://doi.org/10.1109/ISQED57927.2023.10129319.
[5]. Ç. K. Koç, Ed., Cryptographic Engineering, Boston, MA: Springer US, (2009). https://doi.org/ 10.1007/978-0-387-71817-0.
[6]. V. Mannalath, S. Mishra, A. Pathak, A Comprehensive Review of Quantum Random Number Generators: Concepts, Classification and the Origin of Randomness, 22 (2023) 439. https://doi.org/10.1007/s11128-023-04175-y.
[7]. M. A. Wayne, P. G. Kwiat, Low-bias high-speed quantum random number generator via shaped optical pulses, Optics Express, 18 (2010) 9351. https://doi.org/10.1364/OE.18.009351.
[8]. M. Fürst, H. Weier, S. Nauerth, D. G. Marangon, C. Kurtsiefer, H. Weinfurter, High speed optical quantum random number generation, Optics Express, 18 (2010) 13029. https://doi.org/10.1364/OE.18.013029.
[9]. Y. Shen, L. Tian, H. Zou, Practical quantum random number generator based on measuring the shot noise of vacuum states, Physical Review A, 81 (2010) 063814. https://doi.org/10.1103/PhysRevA.81.063814.
[10]. Q. Zhou, R. Valivarthi, C. John, W. Tittel, Practical quantum random number generator based on sampling vacuum fluctuations, 1 (2018) 1-6. http://arxiv.org/abs/1703.00559
[11]. B. Qi, Y.-M. Chi, H.-K. Lo, L. Qian, High-speed quantum random number generation by measuring phase noise of a single-mode laser, Optics Letters, 35 (2010) 312. https://doi.org/10.1364/OL.35.000312.
[12]. W. Wei, G. Xie, A. Dang, H. Guo, High-Speed and Bias-Free Optical Random Number Generator, IEEE Photonics Technology Letters, 24 (2012) 437–439. https://doi.org/10.1109/LPT.2011.2180521.
[13]. Y. Alexeev et al., Quantum Computer Systems for Scientific Discovery, PRX Quantum 2, 2 (2021) 017001. https://doi.org/10.1103/PRXQuantum.2.017001.
[14]. J. Preskill, Quantum Computing in the NISQ era and beyond, 2 (2018) 79. https://doi.org/10.22331/q-2018-08-06-79.
[15]. Y. Wang, Quantum Computation and Quantum Information, Statistical Science, 27 (2012) 373-394. https://doi.org/10.1214/11-STS378.
[16]. L. E. Bassham et al., A statistical test suite for random and pseudorandom number generators for cryptographic applications, Gaithersburg, 20899 (2010) 1-131. https://doi.org/10.6028/NIST.SP.800-22r1a.
[17]. W. Schindler, A Proposal for Functionality Classes for Random Number Generators, (2022) 1-239. https://www.bsi.bund.de/SharedDocs/Downloads/EN/BSI/Certification/Interpretations/AIS_31_Functionality_classes_for_random_number_generators_e.html.
[18]. R. Biswas, D. Roy Talukdar, U. Roy, Verifying the Reliability of Quantum Random Number Generator: A Comprehensive Testing Approach, SN Computer Science, 5 (2024) 140. https://doi.org/10.1007/s42979-023-02323-w.
[19]. M. Wahl, M. Leifgen, M. Berlin, T. Röhlicke, H.-J. Rahn, O. Benson, An ultrafast quantum random number generator with provably bounded output bias based on photon arrival time measurements, Applied Physics Letters, 98 (2011) 171105. https://doi.org/10.1063/1.3578456.
[20]. S. Li, L. Wang, L.-A. Wu, H.-Q. Ma, G.-J. Zhai, True random number generator based on discretized encoding of the time interval between photons, Journal of the Optical Society of America A, 30 (2013) 124. https://doi.org/10.1364/JOSAA.30.000124.
[21]. B. Sanguinetti, A. Martin, H. Zbinden, N. Gisin, Quantum Random Number Generation on a Mobile Phone, Physical Review X, 4 (2014) 031056. https://doi.org/10.1103/PhysRevX.4.031056.
[22]. T. Symul, S. M. Assad, P. K. Lam, Real time demonstration of high bitrate quantum random number generation with coherent laser light, Applied Physics Letters, 98 (2011) 231103. https://doi.org/10.1063/1.3597793.
[23]. Arvind Krishna, 2022 Annual 10-k report, IBM Corporation, (2022). https://www.ibm.com/annualreport/assets/downloads/IBM_Annual_Report_2022.pdf
[24]. L. Huang, H. Zhou, K. Feng, C. Xie, Quantum random number cloud platform, npj Quantum Information, 7 (2021) 107. https://doi.org/10.1038/s41534-021-00442-x.
[25]. Y. Li et al., Analysis of the effects of temperature increase on quantum random number generator, The European Physical Journal D, 75 (2021) 69. https://doi.org/10.1140/epjd/s10053-021-00087-7.
[26]. K. Tamura, Y. Shikano, Quantum Random Number Generation with the Superconducting Quantum Computer IBM 20Q Tokyo, Cryptology ePrint Archive, 30 (2020) 1–13. https://eprint.iacr.org/2020/078
[27]. V. Mannalath, S. Mishra, A. Pathak, A Comprehensive Review of Quantum Random Number Generators: Concepts, Classification and the Origin of Randomness, 22 (2023) 439. http://arxiv.org/abs/2203.00261
[28]. E. F. C. Amira Abbas, Learn Quantum Computation Using Qiskit, (2020). https://qiskit.org/textbook/
[29]. V. Kumar, J. B. B. Rayappan, R. Amirtharajan, P. Praveenkumar, Quantum true random number generation on IBM’s cloud platform, Journal of King Saud University - Computer and Information Sciences, 34 (2022) 6453–6465. https://doi.org/10.1016/j.jksuci.2022.01.015.
[30]. Y. Li et al., Quantum random number generator using a cloud superconducting quantum computer based on source-independent protocol, Scientific Reports, 11 (2021) 23873. https://doi.org/10.1038/s41598-021-03286-9.
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Nhận bài
30/03/2024
Nhận bài sửa
06/05/2024
Chấp nhận đăng
07/05/2024
Xuất bản
15/05/2024
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Kiểu trích dẫn
Nhu Quynh, L., & Van Anh, L. (1715706000). Implement quantum random number generation on the IBM quantum computer platform. Tạp Chí Khoa Học Giao Thông Vận Tải, 75(4), 1644-1658. https://doi.org/10.47869/tcsj.75.4.14
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