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arXiv:2206.02292 · Advanced Quantum Technologies

An Unbiased Quantum Random Number Generator Based on Boson Sampling

Jinjing Shi, Tongge Zhao, Yizhi Wang, Chunlin Yu, Yuhu Lu, Jiajie Wu, Ronghua Shi, Shichao Zhang, Shaoliang Peng, Junjie Wu

Published Oct 25, 2023• 10 citations
arXivHTMLPDF

Abstract

Abstract It is proven that Boson sampling is a much promising model of optical quantum computation, which is applied to designing quantum computer successfully, such as “Jiuzhang” . However, the meaningful randomness of Boson sampling results has not been utilized or exploited. In this research, Boson sampling is applied to design a quantum random number generator (QRNG) by fully exploiting the randomness of Boson sampling results, and its prototype system is constructed with the programmable silicon photonic processor, which can generate unbiased random sequences and overcome the shortcomings of the existing discrete QRNGs such as source‐restricted, high demand for the photon number resolution capability of detector and slow self‐detection generator speed. Boson sampling is implemented as a random entropy source, and random bit strings with satisfactory randomness and uniformity can be obtained after post‐processing the sampling results. It is the first approach for applying the randomness of Boson sampling results to develop a practical prototype system for actual tasks, and the experiment results demonstrate that the designed Boson sampling‐based QRNG prototype system passes 15 tests of the NIST SP 800‐22 statistical test component, which proves that Boson sampling has great potential for practical applications with desirable performance besides quantum advantage.

DOI
10.1002/qute.202300179

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Abstract It is proven that Boson sampling is a much promising model of optical quantum computation, which is applied to designing quantum computer successfully, such as “Jiuzhang” . However, the meaningful randomness of Boson sampling results has not been utilized or exploited. In this research, Boson sampling is applied to design a quantum random number generator (QRNG) by fully exploiting the randomness of Boson sampling results, and its prototype system is constructed with the programmable silicon photonic processor, which can generate unbiased random sequences and overcome the shortcomings of the existing discrete QRNGs such as source‐restricted, high demand for the photon number resolution capability of detector and slow self‐detection generator speed. Boson sampling is implemented as a random entropy source, and random bit strings with satisfactory randomness and uniformity can be obtained after post‐processing the sampling results. It is the first approach for applying the randomness of Boson sampling results to develop a practical prototype system for actual tasks, and the experiment results demonstrate that the designed Boson sampling‐based QRNG prototype system passes 15 tests of the NIST SP 800‐22 statistical test component, which proves that Boson sampling has great potential for practical applications with desirable performance besides quantum advantage.
Abstract Quantum random number generators (QRNGs) are based on naturally random measurement results performed on individual quantum systems. Here, we demonstrate a branching-path photonic QRNG implemented using a Sagnac interferometer with a tunable splitting ratio. The fine-tuning of the splitting ratio allows us to maximize the entropy of the generated sequence of random numbers and effectively compensate for tolerances in the components. By producing single-photons from attenuated telecom laser pulses, and employing commercially-available components we are able to generate a sequence of more than 2 gigabytes of random numbers with an average entropy of 7.99 bits/byte directly from the raw measured data. Furthermore, our sequence passes randomness tests from both the NIST and Dieharder statistical test suites, thus certifying its randomness. Our scheme shows an alternative design of QRNGs based on the dynamic adjustment of the uniformity of the produced random sequence, which is relevant for the construction of modern generators that rely on independent real-time testing of its performance.
Abstract As a fundamental form of information representation, image encryption is a significant research issue in the multimedia era. An image encryption scheme is proposed benefiting from chaotic random behavior characteristics of Boson sampling (BS) probability distribution, where the chaotic random number sequence is used to implement the encryption process including scrambling image pixels and altering the values of pixels. Further, a BS‐based image encryption prototype system is constructed on the programmable silicon photonic processor chip for BS with 5‐mode 2‐photon, which can encrypt 4 × 4 grayscale images. Besides, experiments for encrypting 256 × 256 gray‐scale images with 20‐mode 8‐photon BS are simulated on the StrawberryFields photonic quantum software platform. Numerical analyses demonstrate the proposed scheme has good effectiveness in terms of randomness test, information entropy, histogram, correlation, key space, key sensitivity, and anti‐attack, offering gains in many cryptographic applications. The BS‐based image encryption prototype system extends the application of BS to solve practical problems in addition to proving quantum advantages.
Quantum random number generators (QRNG) are the prime source of randomness, by exploiting the unpredictable nature of Quantum mechanics QRNG aims to provide a string of completely random utterly unpredictable numbers. QRNGs are crucial for cryptography, scientific calculation, simulation, and many more real-world applications. Our Optical Quantum Random Number Generator (OQRNG) utilizes a high-speed pulsating laser, a Polarizing beam splitter (PBS), photodetectors, and advanced signal processing units that capture and digitize random photon intensity forming the raw random bit stream. This technique is famously known as Branching Path Technique. After that, we implement rigorous testing that encompasses the statistical randomness tests developed by National Institute of Standards and Technology (NIST) to ensure the guaranteed ran-domness meets security standards. A user-friendly Graphic user interface (GUI) simplifies interaction with the QRNG allowing the user to configure device settings, monitor system performance, and securely extract random numbers. Our findings help us demonstrate the superiority of QRNGs over classical random number generators, and highlight the potential of photon-based QRNGs and their environmentally friendly and efficient random number generation.
Random number generators (RNGs) are critical for problems involving security and cryptography. Much work has been done with true random number generators (TRNGs) that utilize quantum mechanical phenomena as sources of entropy to generate numbers according to some distribution without any underlying deterministic component. While qubit-based quantum computers can serve as high-quality sources of randomness, their effectiveness is limited by constraints due to their physical construction (e.g. not being feasible at room temperatures) and by the number of qubits that are necessary for fine-grained distributions (the number of bins scale as 2n for a n-qubit implementation). Continuous variable photonic quantum computers offer promising scalability, both from their experimental realization and from the use of linear optical components and photon number resolving detectors to generate varied distributions. We demonstrate that boson-sampling-based approaches realized with photonic quantum computers like the Xanadu X8 machine can be used to generate random numbers in diffuse, hard-to-predict distributions and they can be optimized for transformation to a uniform distribution. Specifically, boson sampling can act as a high-quality source of entropy and we introduce a strategy for scaling our TRNG with further experimental development (both in terms of the number of qumodes available and improvements for photonic components). We compare our results to the performance of qubit-based TRNGs and discuss experimental realizations.
Quantum mechanics offers a fundamentally unpredictable entropy source due to the intrinsic probabilistic nature of quantum measurements, making it attractive for secure random number generation. This paper explores the practicality of generating random numbers from two quantum platforms: gate-based circuits on IBM Quantum and (Gaussian) boson sampling with Xanadu Borealis. We implement simple post-processing methods, including the classic Von Neumann extractor and two tailored variants designed to address the correlated structure of boson sampling outputs. We evaluate debiased output from real quantum hardware using the NIST SP800-22r1a test suite and measure the extraction efficiency of each debiasing method. Results show that, while unbiased bitstreams can be achieved on both platforms, throughput remains low and cost per random bit is high compared to specialized QRNG devices.