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Journal of Military Technology

Survey and Analysis of Optical Implementation of Quantum Random Number Generators

Veronica Cornaciu, Ciprian Răcuciu

Published Jun 27, 2025• 0 citations
Publisher

Abstract

Random Number Generators (QRNGs) represent a promising alternative to classical pseudorandom methods, providing a genuine source of randomness based on the fundamental principles of quantum mechanics.This article investigates a particular class of QRNGs -Optical Quantum Random Number Generators (OQRNGs) -which rely on phenomena such as quantum state superposition, wavefunction collapse, vacuum fluctuations, and Raman scattering to generate random bits.The architecture of these systems is analyzed in detail, along with the types of photon sources and detectors employed, as well as the entropy extraction mechanisms.Through a comparative approach, the advantages and limitations of each technology are highlighted: from the simplicity of implementation in beam-splitter-based generators to the high bit rates and scalability offered by systems using homodyne detection or Raman-based schemes.The study results indicate that OQRNGs can be successfully integrated into critical post-quantum security infrastructures, providing verifiable randomness that is fundamentally irreproducible by algorithmic means.In conclusion, optical quantum random number generators constitute a key step toward enhancing digital security by directly harnessing the fundamental uncertainty inherent in the physical nature of light.

DOI
10.32754/jmt.2025.1.07

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A quantum random number generator (QRNG) based on the quantum nature of vacuum fluctuations allows one to obtain random bit sequences that can be used in applications that require a high degree of randomness.In that type of quantum random generation system, optical beam splitters with two inputs and two outputs are normally used.A comparison of Y-splitter and spatial beam splitters shows that for two types of optical splitters, the quantum mathematical description of output signals is identical.This allows the use of fiber Y-splitters in practical QRNG schemes.The possibility of generating true random bits was demonstrated experimentally by using quantum random number generator based on homodyne detection.
Quantum random number generator (QRNG) allows obtaining true random bit sequences. In QRNG based on quantum nature of vacuum, optical beam splitter with two inputs and two outputs is normally used. We compare mathematical descriptions of spatial beam splitter and fiber Y-splitter in the quantum model for QRNG, based on homodyne detection. These descriptions were identical, that allows to use fiber Y-splitters in practical QRNG schemes, simplifying the setup. Also we receive relations between the input radiation and the resulting differential current in homodyne detector. We experimentally demonstrate possibility of true random bits generation by using QRNG based on homodyne detection with Y-splitter.
The success of cybersecurity security depends on cryptographic protocols because they shield sensitive information as well as communication channels and serve to authenticate procedures. These protocols derive their foundation from producing robust random numbers because these numbers serve as the basis for encryption key creation and digital signature generation along with secure access protocols. Random number generators used traditionally such as PRNGs and HRNGs suffer from determinism, and predictability flaws combined with the risk of outside tampering thus affecting their reliability. The weaknesses in cryptographic security become dangerous because of the rising quantum computer threats that would break current encryption methods. Quantum Random Number Generators (QRNGs) introduce revolutionary changes through the quantum mechanics properties of quantum superposition and photon polarization and vacuum fluctuations for truly random number generation. The use of QRNGs brings high-security benefits by giving algorithms unpredictable outputs that hackers cannot predict nor alter without being detected. Implementing QRNGs in cybersecurity networks enables better encryption algorithms as well as securely protected communication systems with strong resistance against contemporary cyber attacks. This article outlines the advantages of QRNGs over traditional RNGs, applications in cryptographic systems, and how they can protect against threats from emerging quantum computing technologies. It also covers the challenges in implementing QRNGs, including hardware complexity, cost, and integration into existing security infrastructures. As cyber threats continue to evolve, QRNGs represent an important milestone in ensuring robust and future-proof cryptographic security
Quantum random number generators (QRNGs) are currently in high demand across a large number of cryptographic applications as secure sources of true randomness. In this work, we characterize the conditions from which randomness can be extracted in a QRNG based on homodyne measurements of vacuum fluctuations by assessing the impact of experimental limitations, such as the digitizer resolution or the presence of excess local oscillator (LO) noise due to an unbalanced detection. Moreover, we propose an estimation method to quantify the excess entropy contribution introduced by an unbalanced detection and analyze the implementation of the post-processing algorithm. Finally, we submitted the generated numbers to a set of statistical tests to assess the quality of its output randomness and verified that it passes the standard libraries.
This paper presents the design and theoretical framework for a quantum random number generator (QRNG) rooted in the principles of quantum mechanics. The core innovation lies in leveraging the inherent randomness associated with quantum measurement, specifically the uncertainty principle, to generate truly random numbers, a significant departure from the limitations of classical random number generators. The proposed system utilizes a measurement process involving a quantum system, such as a photon polarization or a quantum bit, to produce a sequence of random bits. The generated bits are then processed to eliminate bias and ensure high uniformity. The theoretical analysis focuses on quantifying the randomness inherent in the measurement process and demonstrating the potential for generating high-quality random numbers. This work addresses the growing demand for secure communication, cryptography, and simulation applications that require truly random numbers, offering a fundamentally different approach compared to traditional methods.