Random numbers are indispensable resources for application in modern science and technology. Therefore, a dedicated entropy source is essential, particularly for cryptographic tasks and modern applications. In this work, we experimentally demonstrated a scheme to generate random numbers by multiplexing eight tunnel diodes onto a single circuit. As a result, the data rate of random number generation was significantly enhanced eightfold. In comparison to the original scheme that employed one diode, this multiplexing scheme produced data with higher entropy. These data were then post-processed with the Toeplitz-hashing extractor, yielding final outputs that achieved almost full entropy and passed the U.S. National Institute of Standards and Technology (NIST) Special Publication 800-90B validation. These data also passed the NIST Special Publication 800-22 statistical randomness examination and had no sign of patterns detected from an autocorrelation analysis.
Random numbers are indispensable resources for application in modern science and technology. Therefore, a dedicated entropy source is essential, particularly for cryptographic tasks and modern applications. In this work, we experimentally demonstrated a scheme to generate random numbers by multiplexing eight tunnel diodes onto a single circuit. As a result, the data rate of random number generation was significantly enhanced eightfold. In comparison to the original scheme that employed one diode, this multiplexing scheme produced data with higher entropy. These data were then post-processed with the Toeplitz-hashing extractor, yielding final outputs that achieved almost full entropy and passed the U.S. National Institute of Standards and Technology (NIST) Special Publication 800-90B validation. These data also passed the NIST Special Publication 800-22 statistical randomness examination and had no sign of patterns detected from an autocorrelation analysis.
Random numbers are vital in cryptography, simulation modeling, and gambling. This study presents a scheme for a multi-bit quantum random number generator utilizing X-ray radiation. Using a homemade multi-pixel single-photon detector array, we extract randomness from three modes of X-ray radiation: arrival time, spatial position, and polarization direction. We employ the Toeplitz Matrix Hashing extractor for randomness distillation, resulting in the extraction of 40.4 million random bits at a rate of 33.7 bits per photon. The generated random numbers pass all test criteria in the National Institute of Standards and Technology statistical test suite. Our work paves what we believe to be a novel method for generating multi-bit quantum random numbers, promising enhanced security and reliability in various technological applications.
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.
Abstract Designing novel circuits and models for generating truly random numbers is of great importance. Recent attention has been focused on the idea of using real quantum computers to generate random numbers. In order to generate purely random bits and numbers, one method relies on the natural superposition of quantum gates. Here, we design a Quantum Random Number Generator (QRNG) exploiting combinations of Hadamard and controlled-Hadamard gates in IBM Quantum Experience (QX). In order to verify that the generated bit sequences were truly random, the proposed circuit’s outputs were subjected to the National Institute of Standards and Technology (NIST) test suite. In comparison to previous works, we found that not only had the total number of passed tests increased, but the P-values had also improved in many cases. For example, in the simulation style of the IBM QX, the number of passed tests is 14 out of 15 standard NIST tests. For the experimental mood of the IBM 16Q Melbourne, the number of passed tests is six without using any extractions. Furthermore, one more test is passed by adding Barrier operations to the circuits, and the P-values have increased. As a result, we found that the proposed method had more passed tests than previous works. The average of P-values for the six passed tests in former research for the mood of using a combination of extractors is about 0.43 . However, the best result we can get with our circuits is around 0.60 (the average of P-values for 14 passed tests), which is an improvement of 0.17 compared to former works . Because of this, our circuits are getting ever closer to being a true QRNG.
Abstract Pseudo-random number generators are predominantly utilised as entropy sources in encryption and seeding processes, however, they are deterministic by nature. This paper presents the analysis and design methodology of an on-chip quantum noise source that may suitably be used as an entropy source in true random number generators. Quantum tunnelling is achieved through the strong biasing of a MOS structure to generate gate-referred shot noise. Structures are fabricated in a commercial 40 nm process and the sampled noise is tested against the NIST SP800-90B and SP800-22 test suites, showing a maximal entropy of 0.985 at a bias current of 1500 µA with a consistent pass rate across all NIST tests.
This paper proposes a random number generator based on the quantum tunnel effect that takes place in transistors. The main system is divided into two basic components: the entropy source and the postprocessing block. The quantum tunnel effect is subjected to a random character, which means that electrons have a probability to pass through the potential barrier of the transistor. Theoretically, the measurable output current of the transistor should have a random variance in a predetermined interval, that results into a random sequence. Afterwards, the postprocessing block extracts the bias from the generated array. It is implemented through a hash function which employs the Toeplitz matrix, resulting into a true random sequence. This paper accounts the preliminary stages of development of an original random number generator. The focus was the physical phenomena, the tunnel effect in transistors, and the study of its probability with respect to the device parameters. In terms of postprocessing the main regard was choosing the adequate extraction method for the quantum entropy source. The novelty of the paper is represented by using the tunnel FET as an entropy source and finding a suitable postprocessing model for a higher generation rate.
Quantum random number generators (QRNGs) leverage the inherent unpredictability of quantum mechanical phenomena to produce random numbers. However, the performance of many QRNGs is hindered by limitations such as low generation rates and the bulkiness of systems utilizing single-photon detectors (SPDs). In this study, we present a QRNG that addresses these challenges by using a micro-LED as an entropy source, utilizing the intensity fluctuations of spontaneous emissions. By applying post-processing techniques, our 5 × 5 µm 2 micro-LED-based system achieves a PD bandwidth-limited generation rate of 9.375 Gbit/s while successfully passing the required randomness tests outlined by the National Institute of Standards and Technology (NIST). Importantly, systematic testing across micro-LEDs of varying sizes demonstrates consistently high performance, highlighting the robustness of this approach. The compact, small footprint, scalable design, and surface emission characteristics of micro-LEDs pave the way for the development of parallel QRNG-integrated chips, which hold the potential to deliver ultra-high random number generation rates in practical, miniaturized platforms.