The low-latency requirements of a loophole-free Bell test prohibit time-consuming post-processing steps that are often used to improve the statistical quality of a physical random number generator (RNG). Here we demonstrate a postprocessing-free RNG that produces a random bit within 2.4(2) ns of an input trigger. We use the Allan variance as a tool for characterizing non-idealities in the RNG and designing a feedback mechanism to account for and correct long-term drift. The impact of the feedback on the predictability of the output is less than 6.4 × 107 , and results in a system capable of 24 hour operation with output that is statistically indistinguishable from a balanced Bernoulli process.
The low-latency requirements of a loophole-free Bell test prohibit time-consuming post-processing steps that are often used to improve the statistical quality of a physical random number generator (RNG). Here we demonstrate a postprocessing-free RNG that produces a random bit within 2.4(2) ns of an input trigger. We use the Allan variance as a tool for characterizing non-idealities in the RNG and designing a feedback mechanism to account for and correct long-term drift. The impact of the feedback on the predictability of the output is less than 6.4 × 107 , and results in a system capable of 24 hour operation with output that is statistically indistinguishable from a balanced Bernoulli process.
Abstract From dice to modern electronic circuits, there have been many attempts to build better devices to generate random numbers. Randomness is fundamental to security and cryptographic systems and to safeguarding privacy. A key challenge with random-number generators is that it is hard to ensure that their outputs are unpredictable1–3. For a random-number generator based on a physical process, such as a noisy classical system or an elementary quantum measurement, a detailed model that describes the underlying physics is necessary to assert unpredictability. Imperfections in the model compromise the integrity of the device. However, it is possible to exploit the phenomenon of quantum non-locality with a loophole-free Bell test to build a random-number generator that can produce output that is unpredictable to any adversary that is limited only by general physical principles, such as special relativity1–11. With recent technological developments, it is now possible to carry out such a loophole-free Bell test12–14, 22. Here we present certified randomness obtained from a photonic Bell experiment and extract 1, 024 random bits that are uniformly distributed to within 10−12. These random bits could not have been predicted according to any physical theory that prohibits faster-than-light (superluminal) signalling and that allows independent measurement choices. To certify and quantify the randomness, we describe a protocol that is optimized for devices that are characterized by a low per-trial violation of Bell inequalities. Future random-number generators based on loophole-free Bell tests may have a role in increasing the security and trust of our cryptographic systems and infrastructure.
Applications of randomness such as private key generation and public randomness beacons require small blocks of certified random bits on demand. Device-independent quantum random number generators can produce such random bits, but existing quantum-proof protocols and loophole-free implementations suffer from high latency, requiring many hours to produce any random bits. We demonstrate device-independent quantum randomness generation from a loophole-free Bell test with a more efficient quantum-proof protocol, obtaining multiple blocks of 512 random bits with an average experiment time of less than 5 min per block and with a certified error bounded by 2^{-64}≈5.42×10^{-20}.
This dissertation is the result of research which, although electrical and computer engineering in nature, also aims to improve the performance of many systems in the field of quantum information. For example, random number generators are used in almost all areas of science, and the initial portion of this work details the theory, design, and characterization of two photon-arrival-time quantum random number generators (QRNGs). After the QRNGs were completed, it was realized that their performance was severely limited both by the maximum detection rate of the single-photon detectors used, and the precision at which the arrival times could be resolved. The single-photon detectors used for both QRNGs are single-photon avalanche photodiodes (SPADs), devices which when operated below their breakdown voltage can create a macroscopic amount of current (an avalanche) in response to a single incident photon. Some of this charge can become trapped in defects or impurities; if this trapped charge is released when the SPAD is active, a secondary ‘false’ detection event, or ‘afterpulse’ can occur. To lower the afterpulse probability to reasonable levels (< 1%), we attempted to reduce the amount of avalanche charge by halting its growth promptly with high-speed electronics, so that defects have a lower probability of becoming populated in the first place. Initial results show reductions in afterpulse probability by up to a factor of 12, corresponding to a ~20% decrease in dead time, a value that could be improved further. We developed an FPGA-based time-to-digital converter system for use specifically with SPADs, achieving a time-bin resolution of 100 ps, with lower dead time and higher maximum detection rate than all currently available detection systems. This further allowed for the creation of a new higher-order SPAD characterization technique, which was identified previously unknown subtleties to SPAD operation. Finally, we developed an ultra-low-latency QRNG, which was used in one of the recent loophole-free demonstrations of quantum nonlocality. The final latency was below 2.5 ns, to our knowledge the lowest latency QRNG to date. Of special interest, however, is our subsequent exploration into the characterization of its bit-probability drift using atomic clock stability techniques. By employing the Allan deviation and implementing precision feedback, the additional frequency drift caused by environmental fluctuations is reduced such that the resulting bit stream can pass cryptographic random number tests for sample sizes up to 5 Gb. This system is currently intended for the NIST random-number beacon, a world-wide trusted source of random bits.
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.
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.