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Metrological Analysis of a QRNG Based on the Quandela Photonic Quantum Computer

Muriel A. de Souza, F. P. Agostini, Luiz Vicente Gomes Tarelho

Published Jan 1, 2025• 0 citations
Publisher

Abstract

Quantum random number generators (QRNGs) play a crucial role in cryptography, secure communications, and stochastic simulations. This study presents the metrological characterization of a QRNG implemented on the Quandela photonic quantum computer, available via the cloud. The system generates random sequences using single photons and beam splitters, where quantum superposition ensures a fundamentally probabilistic outcome. A key aspect of this characterization involves defining the sample size and the number of qubits used. The Quandela quantum processor operates with up to six qubits, corresponding to six photons in twelve optical modes. However, the simultaneous use of multiple photons can introduce unintended correlations due to quantum interference, affecting the quality of randomness. To ensure independent bit generation, experiments were conducted with a single photon per measurement, producing one-bit outcomes per detection event. The analysis focuses on repeatability and reproducibility, examining the statistical properties of the generated sequences. Raw sequences underwent randomness testing using NIST SP800-22 and entropy assessment with NIST SP800-90B. Initial results indicate that raw sequences exhibit biases due to imperfections in single-photon sources and optical elements. The sequences generated by the Quandela photonic quantum processor failed most NIST SP800-22 tests, including Frequency (Global and Block), Runs, and Approximate Entropy, with six tests showing a 100% failure rate. Additionally, under the NIST SP800-90B evaluation, 100% of the raw sequences failed the independence and identically distributed (IID) test, highlighting strong correlations and statistical dependencies. To enhance randomness quality, post-processing techniques were applied, including Von Neumann and the combination Samuelson + Von Neumann extractors. These methods significantly improved bit balance and reduced statistical dependencies. After post-processing, all sequences passed the NIST SP800-90B IID test, and the entropy per bit increased to 0.771 ± 0.005 for the Ascella processor, ensuring improved randomness quality. The findings highlight the metrological challenges in QRNGs based on photonic quantum processors, emphasizing the need for rigorous statistical validation. Despite system-specific noise, the quantum origin of randomness remains preserved, ensuring that the extracted sequences retain their fundamental unpredictability. Additionally, limitations associated with photonic quantum systems, such as hardware imperfections, photon losses, and optical misalignment, are discussed in the context of their impact on randomness quality. Despite these limitations, rigorous statistical validation and post-processing enable the generation of high-quality random sequences suitable for cryptographic protocols, secure key distribution, and high-performance computing This study reinforces the importance of metrology in quantum technologies, providing a structured methodology for optimizing QRNG reliability and performance.

DOI
10.59161/qapz5804

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Quantum random number generators (QRNGs) play a crucial role in cryptography, secure communications, and stochastic simulations. This study presents the metrological characterization of a QRNG implemented on the Quandela photonic quantum computer, available via the cloud. The system generates random sequences using single photons and beam splitters, where quantum superposition ensures a fundamentally probabilistic outcome. A key aspect of this characterization involves defining the sample size and the number of qubits used. The Quandela quantum processor operates with up to six qubits, corresponding to six photons in twelve optical modes. However, the simultaneous use of multiple photons can introduce unintended correlations due to quantum interference, affecting the quality of randomness. To ensure independent bit generation, experiments were conducted with a single photon per measurement, producing one-bit outcomes per detection event. The analysis focuses on repeatability and reproducibility, examining the statistical properties of the generated sequences. Raw sequences underwent randomness testing using NIST SP800-22 and entropy assessment with NIST SP800-90B. Initial results indicate that raw sequences exhibit biases due to imperfections in single-photon sources and optical elements. The sequences generated by the Quandela photonic quantum processor failed most NIST SP800-22 tests, including Frequency (Global and Block), Runs, and Approximate Entropy, with six tests showing a 100% failure rate. Additionally, under the NIST SP800-90B evaluation, 100% of the raw sequences failed the independence and identically distributed (IID) test, highlighting strong correlations and statistical dependencies. To enhance randomness quality, post-processing techniques were applied, including Von Neumann and the combination Samuelson + Von Neumann extractors. These methods significantly improved bit balance and reduced statistical dependencies. After post-processing, all sequences passed the NIST SP800-90B IID test, and the entropy per bit increased to 0.771 ± 0.005 for the Ascella processor, ensuring improved randomness quality. The findings highlight the metrological challenges in QRNGs based on photonic quantum processors, emphasizing the need for rigorous statistical validation. Despite system-specific noise, the quantum origin of randomness remains preserved, ensuring that the extracted sequences retain their fundamental unpredictability. Additionally, limitations associated with photonic quantum systems, such as hardware imperfections, photon losses, and optical misalignment, are discussed in the context of their impact on randomness quality. Despite these limitations, rigorous statistical validation and post-processing enable the generation of high-quality random sequences suitable for cryptographic protocols, secure key distribution, and high-performance computing This study reinforces the importance of metrology in quantum technologies, providing a structured methodology for optimizing QRNG reliability and performance.
Abstract Quantum mechanics, characterized by its intrinsically probabilistic nature, offers a promising avenue for random number generation, which is essential for applications such as cryptography and computational simulations. With the recent advancements in quantum computing and simulation, numerous studies have emerged utilizing these methods for the generation of random numbers. This research delves into the exploration of random number generation utilizing the Ascella photonic quantum computer developed by Quandela, renowned for its implementation of single-photon-based qubits. Leveraging both the Ascella photonic simulator (SIM Ascella) and the quantum processing unit (QPU Ascella) within the Perceval framework, this investigation examines the capability to generate random sequences through the superposition of quantum states, generated using photons and beam splitters. The analysis includes a performance comparison between simulations and experimental tests with the quantum computer, subjecting the outcomes to the NIST SP 800-22 randomness tests. While initial simulations suggested a high degree of randomness, practical implementation revealed certain disparities attributed to factors such as decoherence, imperfections in beam splitters and single-photon sources, as well as quantum noise. This study contributes to the understanding of random number generation on quantum platforms, identifying challenges and limitations while providing strategies for future enhancements in this quantum technology.
Random Number Generators (RNGs) are used in various applications, including cryptography, scientific simulations, gaming, and virtual reality. The quality of these random numbers is crucial, especially for computational approaches that rely on unpredictability to produce accurate results. In this thesis, we perform a comprehensive assessment of the quality of a novel Quantum Random Number Generator (QRNG) based on single photon. QRNGs leverage quantum mechanical properties to produce truly random numbers. This ensures high entropy, unpredictability, and security, making QRNGs particularly useful in fields that require high-quality randomness.We evaluate the statistical properties of strings generated by our QRNG and then its practical application by comparing it to traditional Pseudo-Random Number Generators (PRNGs) in Monte Carlo Integration (MCI), a technique that estimates integrals using random sampling. In particular, we use two statistical randomness test suits, namely NIST and Dieharder, to assess the statistical properties of our QRNG. All tests within these tests were passed, confirming that the corresponding QRNG achieves true randomness with sufficient high entropy. Next, we use our QRNG-generated numbers to seed Monte Carlo Integration (MCI) and compare it against results obtained using classical PRNG. The QRNG-based MCI demonstrated more accurate and stable numerical estimates, showing lower error rates and improved convergence compared to PRNG-based simulations.These findings highlight the advantages of QRNGs in enhancing numerical accuracy and computational security. While QRNGs may have slower generation rates than PRNGs, their superior randomness quality allows for more reliable Monte Carlo-based simulations, suggesting that fewer samples may be needed to achieve the same level of accuracy compared to classical PRNGs. This research underscores the potential of QRNG-powered numerical methods, paving the way for their integration into more advanced applications, including scientific computing, financial modeling, and cryptographic security.
Abstract We present a quantum random number generator (QRNG) based on vacuum fluctuations that meets the statistical and structural entropy source validation criteria defined in NIST standards. We measured how optical imbalance in a balanced homodyne detector affects the dominance of vacuum fluctuations over the quadrature-phase noise of the local oscillator. Based on this analysis, we developed a simple and direct method to quantify the relative strength of vacuum noise, enabling precise balancing of the detector to maximize the vacuum fluctuation contribution. Our approach ensures that the raw entropy exhibits negligible auto-correlation and that the output samples are independent and identically distributed (i.i.d.), without relying on external post-processing beyond standard NIST-approved conditioning. Following a symbol-space reduction strategy guided by NIST SP 800-90B, we extract high-quality 8-bit entropy samples from 16-bit raw data. To produce full-entropy outputs, the samples are processed using the 384-bit version of the Secure Hash algorithm 3 (SHA3-384). The resulting quantum random numbers successfully pass all tests in the NIST statistical test suite (NIST SP 800-22) and achieve a generation rate of approximately 4 Gbps. This work demonstrates a practical and fully standards-aligned QRNG implementation using only vacuum fluctuations and vetted conditioning.
In recent years, the advancement of quantum computing technology has posed potential security threats to RSA cryptography and elliptic curve cryptography. In response, the National Institute of Standards and Technology (NIST) published several Federal Information Processing Standards (FIPS) of post-quantum cryptography (PQC) in August 2024, including the Module-Lattice-Based Key-Encapsulation Mechanism (ML-KEM), Module-Lattice-Based Digital Signature Algorithm (ML-DSA), and Stateless Hash-Based Digital Signature Algorithm (SLH-DSA). Although these PQC algorithms are designed to resist quantum computing attacks, they may not provide adequate security in certain specialized application scenarios. To address this issue, this study proposes quantum random number generator (QRNG)-based PQC algorithms. These algorithms leverage quantum computing to generate random numbers, which serve as the foundation for key pair generation, key encapsulation, and digital signature generation. A generalized architecture of QRNG is proposed, along with the design of six QRNGs. Each generator is evaluated according to the statistical validation procedures outlined in NIST SP 800-90B, including tests for verification of entropy sources and independent and identically distributed (IID) outputs. Experimental results assess the computation time of the six QRNGs, as well as the performance of QRNG-based ML-KEM, QRNG-based ML-DSA, and QRNG-based SLH-DSA. These findings provide valuable reference data for future deployment of PQC-based Transport Layer Security in web systems.
Abstract This work presents two significant contributions from the perspectives of quantum random number generator (QRNG) manufacturers and users. For manufacturers, the conventional method of assessing the quantumness of single-photon-based QRNGs through mean and variance comparisons of photon counts is statistically unreliable due to finite sample sizes. Given the sub-Poissonian statistics of single photons, confirming the underlying distribution is crucial for validating a QRNG’s quantumness. We propose a more efficient two-fold statistical approach to ensure the quantumness of optical sources with the desired confidence level. Additionally, we demonstrate that the output of QRNGs from exponential and uniform distributions exhibits similarity under device noise, deriving corresponding photon statistics and conditions for ε-randomness. From the user’s perspective, the fundamental parameters of a QRNG are quantumness, efficiency (entropy and random number generation rate), and cost. Our analysis reveals that these parameters depend on three factors, namely, expected photon count per unit time, external reference cycle duration, and detection efficiency. A lower expected photon count enhances entropy but increases cost and decreases the generation rate. A shorter external reference cycle boosts entropy but must exceed a minimum threshold to minimize timing errors, with minor impacts on cost and rate. Lower detection efficiency enhances entropy and lowers cost but reduces the generation rate. Finally, to validate our results, we perform statistical tests like NIST, Dieharder, AIS-31, ENT etc over the data simulated with different values of the above parameters. Our findings can empower manufacturers to customize QRNGs to meet user needs effectively.
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.