Exploring Quantum Random Number Generators:Insights into Architectures, Trade-offs, andApplications

Abstract:

Random number generators (RNGs) are essential for cryptography, secure communications, and simulations. Their key properties include Uniform Distribution, Independence, Unpredictability, Periodicity, and Efficient Computation. Quantum Random Number Generators (QRNGs) utilize quantum phenomena such as photon counting, vacuum fluctuations, and shot noise to produce true randomness, addressing the limitations of classical pseudorandom generators. This paper highlights the trade-offs between generation speed, hardware complexity, and randomness quality in QRNG architectures. Shot noise-based QRNGs exhibit scalability and robustness, while photon-based systems like ID Quantique's Quantis achieve near-perfect unpredictability but are affected by environmental noise and detector imperfections. Neural network-based testing reveals subtle vulnerabilities in QRNG outputs, underscoring the importance of rigorous evaluation frameworks. Advancements in noise isolation, miniaturization, and certification are pivotal for ensuring reliability in critical applications. The comparative evaluation reveals that shot noise-based systems balance performance and hardware simplicity, while photon-based and vacuum fluctuation-based QRNGs excel in precision at higher costs.

Keywords:

Quantum Random Number Generator (QRNG), True Randomness, Shot Noise, Photon Counting, Randomness Testing, Entanglemen