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.
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.
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.
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 numbers sequences (RNSs) play a vital role in various scientific and engineering applications. They are critical to the integrity of classical and quantum cryptography, the accuracy of mathematical modeling and Monte Carlo simulations, and the core mechanics of applications in fields as diverse as gambling and statistical sampling. While the primary criteria for RNSs sources are their quality and generation rate, their integration into experimental designs is equally significant for many fundamental physical tests and applications. This work presents a comparative analysis of optical random number generation architectures, which can be seamlessly included into various advanced classical and quantum optical experimental schemes. In particular, we evaluate the trade-off between the high generation rate of an attenuated laser (a quasi-single-photon source) and the superior statistical quality of a heralded single-photon source operating at a much lower frequency. To overcome the limitations of each individual source, we propose and examine a novel hybrid architecture that utilizes their mixed radiation, enabling the generation of highquality RNSs at an enhanced rate. Furthermore, we demonstrate that the raw sequences generated by such a source can not only exhibit but, in some cases, even surpass the degree of randomness achieved by sequences processed through powerful randomness extractors.
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.
Random numbers are fundamental elements in different fields of science and technology such as computer simulation like Monte Carlo-method simulation, statistical sampling, cryptography, games and gambling, and other areas where unpredictable results are necessary. Random number generators (RNG) are generally classified as “pseudo”-random number generators (PRNG) and "truly" random number generators (TRNG). Pseudo random numbers are generated by computer algorithms with a (random) seed and a specific formula. The random numbers produced in this way (with a small degree of unpredictability) are good enough for some applications such as computer simulation. However, for some other applications like cryptography they are not completely reliable. When the seed is revealed, the entire sequence of numbers can be produced. The periodicity is also an undesirable property of PRNGs that can be disregarded for most practical purposes if the sequence recurs after a very long period. However, the predictability still remains a tremendous disadvantage of this type of generators. Truly random numbers, on the other hand, can be generated through physical sources of randomness like flipping a coin. However, the approaches exploiting classical motion and classical physics to generate random numbers possess a deterministic nature that is transferred to the generated random numbers. The best solution is to benefit from the assets of indeterminacy and randomness in quantum physics. Based on the quantum theory, the properties of a particle cannot be determined with arbitrary precision until a measurement is carried out. The result of a measurement, therefore, remains unpredictable and random. Optical phenomena including photons as the quanta of light have various random, non-deterministic properties. These properties include the polarization of the photons, the exact number of photons impinging a detector and the photon arrival times. Such intrinsically random properties can be exploited to generate truly random numbers. Silicon (Si) is considered as an interesting material in integrated optics. Microelectronic chips made from Si are cheap and easy to mass-fabricate, and can be densely integrated. Si integrated optical chips, that can generate, modulate, process and detect light signals, exploit the benefits of Si while also being fully compatible with electronic. Since many electronic components can be integrated into a single chip, Si is an ideal candidate for the production of small, powerful devices. By complementary metal-oxide-semiconductor (CMOS) technology, the fabrication of compact and mass manufacturable devices with integrated components on the Si platform is achievable. In this thesis we aim to model, study and fabricate a compact photonic quantum random number generator (QRNG) on the Si platform that is able to generate high quality, "truly" random numbers. The proposed QRNG is based on a Si light source (LED) coupled with a Si single photon avalanche diode (SPAD) or an array of SPADs which is called Si photomultiplier (SiPM). Various implementations of QRNG have been developed reaching an ultimate geometry where both the source and the SPAD are integrated on the same chip and fabricated by the same process. This activity was performed within the project SiQuro—on Si chip quantum optics for quantum computing and secure communications—which aims to bring the quantum world into integrated photonics. By using the same successful paradigm of microelectronics—the study and design of very small electronic devices typically made from semiconductor materials—, the vision is to have low cost and mass manufacturable integrated quantum photonic circuits for a variety of different applications in quantum computing, measure, sensing, secure communications and services. The Si platform permits, in a natural way, the integration of quantum photonics with electronics. Two methodologies are presented to generate random numbers: one is based on photon counting measurements and another one is based on photon arrival time measurements. The latter is robust, masks all the drawbacks of afterpulsing, dead time and jitter of the Si SPAD and is effectively insensitive to ageing of the LED and to its emission drifts related to temperature variations. The raw data pass all the statistical tests in national institute of standards and technology (NIST) tests suite and TestU01 Alphabit battery without a post processing algorithm. The maximum demonstrated bit rate is 1.68 Mbps with the efficiency of 4-bits per detected photon. In order to realize a small, portable QRNG, we have produced a compact configuration consisting of a Si nanocrystals (Si-NCs) LED and a SiPM. All the statistical test in the NIST tests suite pass for the raw data with the maximum bit rate of 0.5 Mbps. We also prepared and studied a compact chip consisting of a Si-NCs LED and an array of detectors. An integrated chip, composed of Si p+/n junction working in avalanche region and a Si SPAD, was produced as well. High quality random numbers are produced through our robust methodology at the highest speed of 100 kcps. Integration of the source of entropy and the detector on a single chip is an efficient way to produce a compact RNG. A small RNG is an essential element to guarantee the security of our everyday life. It can be readily implemented into electronic devices for data encryption. The idea of "utmost security" would no longer be limited to particular organs owning sensitive information. It would be accessible to every one in everyday life.
This paper explores the generation of high-quality random numbers utilizing the principles of quantum chaos. Traditional random number generators often exhibit limitations in terms of randomness and predictability, posing challenges for applications in secure communication and cryptography. This research investigates the potential of quantum chaos to overcome these limitations, proposing a novel approach based on quantum chaotic algorithms. The core of this approach lies in the generation of sequences exhibiting chaotic properties, subsequently analyzed to extract random numbers. The generated numbers are characterized by their enhanced randomness and unpredictability, offering a significant advancement over conventional methods. This work outlines the theoretical framework, the underlying mathematical principles, and the potential applications of quantum chaotic random number generation. The primary goal is to demonstrate a method capable of producing truly random sequences, crucial for secure systems.