Random numbers are an essential resource to many applications, including cryptography and Monte Carlo simulations. Quantum random number generators (QRNGs) represent the ultimate source of randomness, as the numbers are obtained by sampling a physical quantum process that is intrinsically probabilistic. However, they are yet to be widely employed to replace deterministic pseudo random number generators (PRNG) for practical applications. QRNGs are regarded as interesting devices. However, they are slower than PRNGs for simulations and are typically seen as clumsy laboratory prototypes, prone to failures, and unreliable for cryptographic applications. Here, we overcome these limitations and demonstrate a compact and self-contained QRNG capable of generating random numbers at a pace of 8 Gbit/s uninterruptedly for 71 days. During this period, the physical parameters of the quantum process were monitored in real time by self-checking functions implemented in the generator itself. At the same time, the output random numbers were analyzed with the most stringent suites of statistical tests. The analysis shows that the QRNG under test sustained the continuous operation without physical instabilities or hardware failures. At the same time, the output random numbers were analyzed with the most stringent suites of statistical tests, which were passed during the whole operation time. This extensive trial demonstrates the reliability of a robustly designed QRNG and paves the way to its use in practical applications based on randomness.
Random numbers are an essential resource to many applications, including cryptography and Monte Carlo simulations. Quantum random number generators (QRNGs) represent the ultimate source of randomness, as the numbers are obtained by sampling a physical quantum process that is intrinsically probabilistic. However, they are yet to be widely employed to replace deterministic pseudo random number generators (PRNG) for practical applications. QRNGs are regarded as interesting devices. However, they are slower than PRNGs for simulations and are typically seen as clumsy laboratory prototypes, prone to failures, and unreliable for cryptographic applications. Here, we overcome these limitations and demonstrate a compact and self-contained QRNG capable of generating random numbers at a pace of 8 Gbit/s uninterruptedly for 71 days. During this period, the physical parameters of the quantum process were monitored in real time by self-checking functions implemented in the generator itself. At the same time, the output random numbers were analyzed with the most stringent suites of statistical tests. The analysis shows that the QRNG under test sustained the continuous operation without physical instabilities or hardware failures. At the same time, the output random numbers were analyzed with the most stringent suites of statistical tests, which were passed during the whole operation time. This extensive trial demonstrates the reliability of a robustly designed QRNG and paves the way to its use in practical applications based on randomness.
Random numbers are essential for our modern information based society e.g. in cryptography. Unlike frequently used pseudo-random generators, physical random number generators do not depend on complex algorithms but rather on a physical process to provide true randomness. Quantum random number generators (QRNG) do rely on a process, which can be described by a probabilistic theory only, even in principle. Here we present a conceptually simple implementation, which offers a 100% efficiency of producing a random bit upon a request and simultaneously exhibits an ultra low latency. A careful technical and statistical analysis demonstrates its robustness against imperfections of the actual implemented technology and enables to quickly estimate randomness of very long sequences. Generated random numbers pass standard statistical tests without any post-processing. The setup described, as well as the theory presented here, demonstrate the maturity and overall understanding of the technology.
Random numbers play an important role in many areas, for example, encryption, cryptography, static analysis, simulations.It is also a fundamental resource in science and engineering.There are algorithmically generated numbers that are similar to random distributions, but are not actually random, called pseudo random number generators.In many cases the tasks to be solved are based on the unpredictability of random numbers, which cannot be guaranteed in the case of pseudo random number generators, true randomness is required.In such situations, we use real random number generators whose source of randomness is unpredictable random events.Quantum Random Number Generators (QRNGs) generate real random numbers based on the inherent randomness of quantum measurements.Our goal is to generate fast random numbers at a lower cost.At the same time, a high level of randomness is essential.Through quantum mechanics, we can obtain true numbers using the unpredictable behavior of a photon, which is the basis of many modern cryptographic protocols.It is essential to trust cryptographic random number generators to generate only true random numbers.This is why certification methods are needed which will check both the operation of the device and the quality of the random bits generated.We present the improved novel quantum random number generator, which is based the on time of arrival QRNG.It uses the simple version of the detectors with few requirements.The novel QRNG produces more than one random bit per each photon detection.It is rather efficient and has a high level of randomness.Self-testing as well as device independent quantum random number generation methods are analyzed.The advantages and disadvantages of both methods are identified.The model of a novel semi self-testing certification method for quantum random number generators (QRNG) is offered in the paper.This method combines different types of certification approaches and is rather secure and efficient.Finally, the novel certification method is integrated into the model of the new quantum random number generator.The paper analyzes its security and efficiency.
Quantum random number generators (QRNG) provide quality random numbers, which are essential for cryptography by utilizing the unpredictable nature of quantum mechanics.Advancements in quantum optics made multiple different architectures for these possible.As part of a project aiming to realize a QRNG service, we developed a system capable of providing real-time monitoring and long term data collection while still fulfilling regular processing duties for these devices.In most cases, hardware validation is done by simply running a battery of statistical tests on the final output.Our goal, however, was to create a system allowing more flexible use of these tests, realizing a tool that can also prove useful during the construction of our entropy source for detecting and correcting unique imperfections.We tested this flexibility and the system's ability to adequately perform the required tasks with simulated sources while further examining the usability of available verification tools within this new custom framework.
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 a fundamental resource in science and engineering, and are also widely used in many fields, such as simulation, cryptography, lotteries, fundamental science. There are algorithmically generated numbers that look like random numbers but are not truly random. These pseudo random numbers are generated from a computer, using deterministic algorithms. Because, we cannot use pseudo random generators in situations, where true randomness is necessary, we use true random number generators. In this case, we use unpredictable random events as a random source. Quantum random number generators (QRNG) output true random numbers based on inherent randomness in quantum measurements. Our goal is to generate fast random numbers at a lower cost. At the same time, a high level of randomness is essential. We present the improved novel quantum random number generator, which is based the on time of arrival QRNG. It is rather efficient, as it uses the simple version of the detectors with rather few requirements. The novel QRNG produces more than one random bit per each photon detection.
The subject matter of the article is pseudo-random number generators. Random numbers play the important role in cryptography. Using not secure pseudo-random number generators is a very common weakness. It is also a fundamental resource in science and engineering. There are algorithmically generated numbers that are similar to random distributions but are not random, called pseudo-random number generators. In many cases the tasks to be solved are based on the unpredictability of random numbers, which cannot be guaranteed in the case of pseudo-random number generators, true randomness is required. In such situations, we use real random number generators whose source of randomness is unpredictable random events. Quantum Random Number Generators (QRNGs) generate real random numbers based on the inherent randomness of quantum measurements. The goal is to develop a mathematical model of the generator, which generates fast random numbers at a lower cost. At the same time, a high level of randomness is essential. Through quantum mechanics, we can obtain true numbers using the unpredictable behavior of a photon, which is the basis of many modern cryptographic protocols. It is essential to trust cryptographic random number generators to generate only true random numbers. This is why certification methods are needed which will check both the operation of the device and the quality of the random bits generated. The goal of the research is also to develop the model of a hybrid semi self-testing certification method for quantum random number generators (QRNG). The tasks to be solved are to create the mathematical model of a random number generator, which generates the fast random numbers at a lower cost. To create the mathematical model of a hybrid semi self-testing certification method for quantum random number generators. To integrate a hybrid semi self-testing certification method to the hybrid random number generator. the methods used are mathematical optimization and simulation. The following results were obtained: we present the improved hybrid quantum random number generator, which is based on QRNG, which uses the time of arrival of photons. The model of a hybrid semi self-testing certification method for quantum random number generators (QRNG) is offered in the paper. This method combines different types of certification approaches and is rather secure and efficient. Finally, the hybrid certification method is integrated into the model of the new quantum random number generator. Conclusions. The scientific novelty of the results obtained is as follows: 1. The hybrid quantum random number generator is offered, which is based on QRNG, which uses the time of the arrival of photons. It uses the simple version of the detectors with few requirements. The hybrid QRNG produces more than one random bit per the detection of each photon. It is rather efficient and has a high level of randomness. 2. The hybrid semi self-testing certification method for quantum random number generators (QRNG) is offered. The Self-testing, as well as device-independent quantum random number generation methods, are analyzed. The advantages and disadvantages of both methods are identified. Based on the result the hybrid method is offered. 3. The hybrid semi self-testing certification method for quantum random number generators is integrated into the offered model of the quantum random number generator. The paper analyzes its security and efficiency. The paper offers to use the new random number generator in the crypto-schemes.