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IEEE photonics journal

High-Speed and Scalable Quantum Random Number Generation Using InGaN Micro-LEDs

Fu‐He Hsiao, Yun-Han Chang, Hung Chou, Ching-Chang Hsiao, Boon S. Ooi, Chun-Liang Lin, Chi-Wai Chow, Yu-Heng Hong, Hao‐Chung Kuo

Published Feb 24, 2026• 0 citations
Publisher

Abstract

This paper presents a high-speed and scalable quantum random number generator (QRNG) based on InGaN micro-LED arrays. While traditional QRNG systems face limitations in data rate and integration complexity, our approach leverages the intrinsic quantum randomness of spontaneous emission from micro-LEDs to achieve superior performance. We successfully demonstrated a generation rate of 12.5 Gb/s with a single blue and green micro-LED, as well as with a 2×4 yellow micro-LED array. The randomness of the generated bit streams was validated by the NIST SP800-22 statistical test suite under the assumed trusted-device model, confirming their high quality and cryptographic suitability. The use of a multi-channel array further proves the scalability of our method, highlighting its potential for seamlessly boosting generation rates. In particular, this work demonstrates the potential of micro-LED-based QRNGs toward compact and high-performance implementations, paving the way for on-chip integration into future cryptographic and communication applications.

DOI
10.1109/jphot.2026.3667536

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This paper presents a high-speed and scalable quantum random number generator (QRNG) based on InGaN micro-LED arrays. While traditional QRNG systems face limitations in data rate and integration complexity, our approach leverages the intrinsic quantum randomness of spontaneous emission from micro-LEDs to achieve superior performance. We successfully demonstrated a generation rate of 12.5 Gb/s with a single blue and green micro-LED, as well as with a 2×4 yellow micro-LED array. The randomness of the generated bit streams was validated by the NIST SP800-22 statistical test suite under the assumed trusted-device model, confirming their high quality and cryptographic suitability. The use of a multi-channel array further proves the scalability of our method, highlighting its potential for seamlessly boosting generation rates. In particular, this work demonstrates the potential of micro-LED-based QRNGs toward compact and high-performance implementations, paving the way for on-chip integration into future cryptographic and communication applications.
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.
Quantum random number generators (QRNGs) harness the inherent unpredictability of quantum processes to generate true randomness, a critical resource for cryptography, secure communications, and emerging quantum technologies. In this paper, I will present a compact and scalable QRNG architecture based on micro-light-emitting diodes (micro-LEDs), which serve as entropy sources by exploiting the intensity fluctuations of spontaneous emission. Our system, using a micro-LED, achieves a bandwidth-limited generation rate of 9.375 Gbit/s, while meeting the statistical randomness requirements specified by the NIST test suite. Our work lays the foundation for parallel QRNG integration on chip, enabling ultra-high-rate quantum random number generation in miniaturized, energy-efficient, and practical platforms. The implications of this advancement span from secure data and hardward to next-generation cryptographic systems.
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.
Random number generation is a fundamental task for modern cryptography, secure communications, and stochastic computing. Quantum random number generators (QRNGs) provide inherently unpredictable data derived from quantum physical processes and therefore offer stronger security guarantees than classical approaches. However, some optical QRNGs rely on blue light-emitting diodes (LEDs), which suffer from reduced spectral matching with commonly used silicon avalanche photodiodes (APDs). This mismatch restricts the achievable signal-to-noise ratio (SNR) and limits the extractable quantum entropy. Here, we demonstrate a spontaneous emission-based QRNG employing a green InGaN LED coupled to a silicon APD. The improved spectral overlap between the emitted light and the APD responsivity results in a significantly higher SNR than with previously reported blue LEDs operating at similar electrical power levels. The measured signal is first filtered with a high-pass filter to suppress low-frequency noise, then randomness is extracted using the SHAKE256 hash function. A detailed statistical and spectral analysis is performed to evaluate the extractable entropy of the generated data. A physically reasonable estimation yields a quantum entropy generation rate of 2.78 Gbit/s. These results establish longer-wavelength nitride-based LEDs as a more suitable entropy source for QRNG systems, using inexpensive and widely available silicon photodiodes.
The security of electronic devices has become a key requisite for the rapidly-expanding pervasive and hyper-connected world. Robust security protocols ensuring secure communication, device's resilience to attacks, authentication control and users privacy need to be implemented. Random Number Generators (RNGs) are the fundamental primitive in most secure protocols but, often, also the weakest one. Establishing security in billions of devices requires high quality random data generated at a sufficiently high throughput. On the other hand, the RNG should exhibit a high integration level with on-chip extraction to remove, in real time, potential imperfections. We present the first integrated Quantum RNG (QRNG) in a standard CMOS technology node. The QRNG is based on a parallel array of independent Single-Photon Avalanche Diodes (SPADs), homogeneously illuminated by a DC-biased LED, and co-integrated logic circuits for postprocessing. We describe the randomness generation process and we prove the quantum origin of entropy. We show that co-integration of combinational logic, even of high complexity, does not affect the quality of randomness. Our CMOS QRNG can reach up to 400 Mbit/s throughput with low power consumption. Thanks to the use of standard CMOS technology and a modular architecture, our QRNG is suitable for a highly scalable solution.