Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On the other hand, True Random Number Generation (TRNG) offers true randomness. One way of obtaining such randomness are quantum systems, including quantum computers. As such the use of quantum computers for TRNG has received considerable attention in recent years. However, existing studies almost exclusively consider IBM quantum computers, often stop at using simulations and usually test only a handful of different TRNG quantum circuits. In this paper, we address those issues by presenting a study of TRNG circuits on Odra 5 a real-life quantum computer installed at Wrocław University of Science and Technology. It is also the first study to utilize the IQM superconducting architecture. Since Odra 5 is available on-premises it allows for much more comprehensive study of various TRNG circuits. In particular, we consider 5 types of TRNG circuits with 105 circuit subvariants in total. Each circuit is used to generate 1 million bits. We then perform an analysis of the quality of the obtained random sequences using the NIST SP 800-22 and NIST SP 800-90B test suites. We also provide a comprehensive review of existing literature on quantum computer-based TRNGs.
翻译:随机数生成是密码学、模拟仿真和机器学习等众多现代应用的基础。传统的伪随机数虽能提供统计上的不可预测性,但其本质仍是确定性的。相比之下,真随机数生成(TRNG)能产生真正的随机性。量子系统(包括量子计算机)是实现此类随机性的途径之一。因此,近年来利用量子计算机进行TRNG的研究备受关注。然而,现有研究几乎全部集中于IBM量子计算机,通常仅停留在模拟阶段,且仅测试少数几种TRNG量子电路。本文针对上述问题,通过在弗罗茨瓦夫理工大学部署的真实量子计算机Odra 5上开展TRNG电路研究。本研究亦是首次利用IQM超导架构的探索。由于Odra 5支持本地部署,使得对各种TRNG电路进行更全面的研究成为可能。具体而言,我们考察了5类TRNG电路,共计105种子电路变体。每个电路用于生成100万比特数据,随后采用NIST SP 800-22与NIST SP 800-90B测试套件对所得随机序列的质量进行分析。本文还系统综述了现有基于量子计算机的TRNG相关文献。