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Chinese Physics Letters

A High-Randomness and High-Stability Electronic Quantum Random Number Generator without Post Processing

Yu-Xuan Liu, Ke-Xin Huang, Yuming Bai, Zhe Yang, Junlin Li

Published Jun 1, 2023• 7 citations
Publisher

Abstract

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.

DOI
10.1088/0256-307x/40/7/070303

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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.
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.
A quantum random number generator (QRNG) based on a silicon nanocrystals (Si-NCs) light emitting device (LED) coupled with a silicon single photon avalanche photodiode (Si-SPAD) is presented. A simple setup is used for the generation of random bits. The modeled approach assures a negligible bias on datasets of 100 Mbits length. The raw data pass all the statistical tests in the National Institute of Standards and Technology (NIST) suite without any post-processing operations. The bit-rate of 0.6 Mbps is achieved. The information-theoretically provable randomness extractor of Toeplitz-hashing function is applied to longer datasets (1 Gbits) to extract the randomness, to minimize the bias, and consequently pass all the NIST tests. Stabilizing the temperature, resetting the applied current to the LED, or a feedback system can also be used as parameter control solutions to generate good quality, long datasets of random numbers suitable for cryptographic applications.
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 generated via quantum process is indeterministic, which are of essential to the cryptographic communication and the large-scale computer modeling. However, in realistic scenarios, classical noises can inevitably contaminate the raw sequences of a quantum randomness number generator (QRNG), and then compromise the security of the QRNG. Min-entropy is a useful approach that can quantify the randomness independent of side-information. To enhance the extractable randomness of the raw sequences arising from the QRNG, we propose a new method which exploits non-uniform quantization methods instead of uniform sampling methods and effectively enhances the extractable randomness from the QRNG at a high quantum-to-classical-noise ratio (QCNR). Given a QCNR as 50 dB and a 16-bit analog-to-digital converter (ADC), the worst-case conditional min-entropy of the non-uniform quantization scheme is improved by nearly 11% compared with that of the uniform sampling scheme.
Quantum random-number generators (QRNGs) produce true random numbers, which are guaranteed by the fundamental principles of quantum physics. Miniaturization of QRNGs is crucial for a wide range of communication and cryptography applications. Here, we first report a fully functional QRNG chip based on vacuum-state fluctuations, with dimensions of $16.6\ifmmode\times\else\texttimes\fi{}7.8\phantom{\rule{0.2em}{0ex}}{\mathrm{mm}}^{2}$. The quantum entropy source, which is achieved via hybrid photonic integration with an SiO2{\mathrm{Si}\mathrm{O}}_{2}SiO2​ waveguide, generates raw quantum random numbers. The hybrid photonic and electrical components are assembled into a compact ceramic package using system-in-package technology. A microcontroller unit acquires the raw data and outputs the processed quantum random numbers via a serial peripheral interface. According to the characterization results, the QRNG chip achieves a constant real-time output rate of 5.2 Mbps across the industrial temperature range of $\ensuremath{-}40$ to $85{\phantom{\rule{0.1em}{0ex}}}^{\ensuremath{\circ}}\mathrm{C}$, making it suitable for practical applications.