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Gallium Nitride Materials and Devices

Scalable high-speed quantum random number generation using micro-LED entropy sources

Boon S. Ooi

Published Mar 5, 2026• 0 citations
Publisher

Abstract

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.

DOI
10.1117/12.3085321

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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.
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.
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.
Abstract Secure communication in Internet-of-Things (IoT) systems typically rely on separate hardware elements for key generation, device authentication, and data transmission, complicating scalable integration. Here we demonstrate that micro-LEDs can integrate all three capabilities, reducing energy and footprint overheads and avoiding exposure to additional attack surfaces. Notably, fabrication-induced structural variations can generate stable, device-unique near-field emission patterns that serve as optoelectronic physical unclonable functions (PUFs), while spontaneous-emission noise can provide a quantum-origin entropy source for quantum random number generators (QRNGs). Through min-entropy evaluation and post-processing, a single micro-LED delivers a stable QRNG throughput of 13.25 Gb/s. Using a deep-neural-network-assisted extractor, each device yields reproducible 256-bit keys, with intra- and inter-device Hamming distances separated by more than an order of magnitude. Integrated into a post-quantum cryptographic framework, the micro-LED functions as a self-contained secure transmitter, enabling authenticated and encrypted free-space optical wireless communication at 1.97 Gb/s. In principle, the security mechanisms are wavelength-independent and extendable across material platforms. Together, these results establish a quantum-resilient photonic node that consolidates transmission, identity, and randomness at the edge device level, providing a scalable hardware building block for secure, low-power connectivity in future IoT networks.
One of the solutions to the problem of secure communication is the Quantum Random Number Generators (QRNGs) which generate true randomness based on quantum mechanical principles.QRNGs are different from conventional pseudo random number generator in that they use quantum uncertainty to generate outputs which are very unpredictable.This work attempts to examine different QRNG architectures, study the possible integration of cryptographic frameworks with these architectures and highlight potential vulnerabilities in the integration of cryptographic frameworks with QRNG architectures.Post-processing techniques, i.e.Zero-Phase Component Analysis (ZPCA) and neural network based techniques are also studied to increase entropy and suppress environmental noise in QRNG systems.Key findings show that system jitter models based QRNG architectures are more scalable and less expensive for use in real world applications.Additionally, incorporating cryptographic protocols with the QRNGs endows them with the ability to resist quantum threats, and hence, provide better key distribution in the secure IoT communication frameworks.However, as security problems such as side channel attacks and hardware manipulation are still big issues.It also points out some of the emerging research trends including hybrid QRNG architectures, i.e., QRNG with classical PRNG to increase the entropy rate.As such, the proposed methodologies attempt to enhance QRNG scalability, security, and energy efficiency in cloud infrastructures, in mobile systems and in critical security environments.The advancement of these technologies will assume a crucial function in the advancement of quantum-safe frames for current advanced computerized foundation.
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.