Utilizing the inherently unpredictable nature of quantum mechanics, quantum random number generators (QRNGs) can provide randomness for applications where quality entropy (like in the case of cryptography) is essential. We present a post-processing scheme utilizing min-entropy estimation and hashing for optical QRNGs based on measuring individual photon arrival times. Our method allows for the handling of possible errors due to non-ideal components or even a potential attacker, given some basic assumptions to reliably produce a safe, good quality, uniformly distributed bitstream as output. We validate our results with an intentionally non-ideal measurement setup to show robustness, while also statistically testing our final output with four popular statistical test suites.
Utilizing the inherently unpredictable nature of quantum mechanics, quantum random number generators (QRNGs) can provide randomness for applications where quality entropy (like in the case of cryptography) is essential. We present a post-processing scheme utilizing min-entropy estimation and hashing for optical QRNGs based on measuring individual photon arrival times. Our method allows for the handling of possible errors due to non-ideal components or even a potential attacker, given some basic assumptions to reliably produce a safe, good quality, uniformly distributed bitstream as output. We validate our results with an intentionally non-ideal measurement setup to show robustness, while also statistically testing our final output with four popular statistical test suites.
Quantum random number generators can deliver entropy based on inherently non-deterministic physical phenomena, which is essential for applications where quality randomness is needed (e.g. in cryptography). Our generator based on photon time-of-arrival exploits the randomness of light emission in semiconductors. To measure the time between detections we use a continuous (non-restartable) clock for time tagging, which permits simpler hardware but produces slightly different output from the optimal exponential distribution. To handle this and produce quality output, we use Toeplitz hashing based bit generation after modeling and calculating a lower bound of extractable min-entropy for the general case of this generation scheme with a continuous clock. We produced uniformly distributed output bits with our setup, while also reaching a generation efficiency of 9.75 output bits per 16-bit input record, which is an improvement to our previously used method. Our generator has also been statistically tested using four of the popular statistical test suites.
Quantum random number generators offer various ways of generating entropy based on inherently nondeterministic physical processes, thus guaranteeing the quality and security of their output. While the expected output of random number generators is a uniformly distributed stream of bits, actual physical measurement statistics typically follow some other distribution, mandating additional post-processing steps. We present a post-processing scheme inspired by the continuous probability integral transform that can be used with the typically discrete distributions of physical measurement statistics to produce a close to uniformly distributed output bitstream. We give bounds on the maximum bias of the output and also show a way to produce output that is arbitrarily close statistically to the expected uniform distribution in an ideal scenario. While the scheme can be used with any input distribution, we utilized a photonic time-of-arrival based architecture to give a practical example of usage and acquire experimental results, which we statistically tested with the NIST Statistical Test Suite.
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 numbers are one of the key foundations of cryptography. This work implements a discrete quantum random number generator (QRNG) based on the tunneling effect of electrons in an avalanche photo diode. Without any post-processing and conditioning, this QRNG can output raw sequences at a rate of 100 Mbps. Remarkably, the statistical min-entropy of the 8,000,000 bits sequence reaches 0.9944 bits/bit, and the min-entropy validated by NIST SP 800-90B reaches 0.9872 bits/bit. This metric is currently the highest value we have investigated for QRNG raw sequences. Moreover, this QRNG can continuously and stably output raw sequences with high randomness over extended periods. The system produced a continuous output of 1,174 Gbits raw sequence for a duration of 11,744 s, with every 8 Mbits forming a unit to obtain a statistical min-entropy distribution with an average value of 0.9892 bits/bit. The statistical min-entropy of all data (1,174 Gbits) achieves the value of 0.9951 bits/bit. This QRNG can produce high-quality raw sequences with good randomness and stability. It has the potential to meet the high demand in cryptography for random numbers with high quality.
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.
Quantum random number generation (QRNG) relies on the inherent unpredictability of quantum mechanical phenomena to efficiently generate high-quality random numbers that can be used in a wide range of cryptography and simulation applications. Here we report the experimental demonstration of QRNG from the arrival times of photons emitted by nitrogen vacancy (NV) centres in fluorescent nanodiamonds. The generation rates achieved range from 0.173 Mbits/s for a region with a single NV centre to 4.77 Mbits/s for a region with just under 50 NV centres, where the latter demonstrates an order of magnitude improvement compared to the highest generation rate previously achieved with NV centres. For all the regions investigated, the generated bits passed the ENT and NIST Statistical Test Suites without post-processing. The results are consistent with our theoretical analysis, where we show that the min-entropy is very close to the ideal value of one per bit for all the regions investigated. This work opens up new possibilities for robust QRNG in highly compact on-chip settings.