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Engineering a Phase-Noise-Based Quantum Random Number Generator for Real-Time Secure Applications: Design, Validation, and Scalability

Anurag K. S. V., Shubham Chouhan, K. Srinivasan, G. Raghavan, Kanaka Raju P

Abstract

Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random Number Generators (PRNGs), True Random Number Generators (TRNGs), and Quantum Random Number Generators (QRNGs). This work presents the end-to-end development of a high-speed, high-efficiency, phase-noise-based QRNG system that taps into the quantum phase noise of a single-frequency laser, with randomness originating from spontaneous emission. Using a self-heterodyne measurement with a semiconductor laser (linewidth $\approx$ 5.23 $GHz$) operated near threshold and a $\sim$48 $cm$ fiber delay line, a raw data generation rate of 2.0 $Gbps$ is achieved. To ensure uniform randomness in the QRNG output, robust extraction techniques developed in-house, such as the Toeplitz Strong Extractor (TSE), are used. Randomness validation using the NIST and Diehard test suites confirms that all statistical tests pass at standard confidence levels. The developed system achieves a post-processed generation rate of 1.0 $Gbps$ in operation and attains a Technology Readiness Level (TRL) of 7, approaching TRL 8, making it suitable for real-time secure applications such as cryptographic key generation and stochastic modeling.

Engineering a Phase-Noise-Based Quantum Random Number Generator for Real-Time Secure Applications: Design, Validation, and Scalability

Abstract

Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random Number Generators (PRNGs), True Random Number Generators (TRNGs), and Quantum Random Number Generators (QRNGs). This work presents the end-to-end development of a high-speed, high-efficiency, phase-noise-based QRNG system that taps into the quantum phase noise of a single-frequency laser, with randomness originating from spontaneous emission. Using a self-heterodyne measurement with a semiconductor laser (linewidth 5.23 ) operated near threshold and a 48 fiber delay line, a raw data generation rate of 2.0 is achieved. To ensure uniform randomness in the QRNG output, robust extraction techniques developed in-house, such as the Toeplitz Strong Extractor (TSE), are used. Randomness validation using the NIST and Diehard test suites confirms that all statistical tests pass at standard confidence levels. The developed system achieves a post-processed generation rate of 1.0 in operation and attains a Technology Readiness Level (TRL) of 7, approaching TRL 8, making it suitable for real-time secure applications such as cryptographic key generation and stochastic modeling.

Paper Structure

This paper contains 13 sections, 9 equations, 8 figures, 3 tables.

Table of Contents

  1. INTRODUCTION
  2. QRNG SUBSYSTEMS CHARACTERIZATION
  3. Laser System
  4. Unbalanced Mach-Zehnder Interferometer Design
  5. High-Speed Photodiode
  6. Oscilloscope
  7. DESIGN OF THE PHASE-NOISE-BASED QRNG
  8. Sampling Rate Matching
  9. Phase Noise Measurement and Optimization of Quantum Noise
  10. RF Spectrum Analysis
  11. Raw Data Acquisition and Normalization
  12. Post-Processing, Validation and System Packaging
  13. CONCLUSION AND FUTURE SCOPE

Figures (8)

  • Figure 1: Various paradigms of QRNGs include fully device-independent QRNGs (FDI-QRNGs), semi-device-independent QRNGs (SDI-QRNGs), and trusted-device QRNGs (TD-QRNGs). SDI-QRNGs are further divided into source and measurement subgroups.
  • Figure 2: Packaged phase-noise-based QRNG schematic. Components include a distributed feedback (DFB) laser source, a delayed Mach-Zehnder interferometer, a photodiode, an analog-to-digital converter (ADC), and a field-programmable gate array (FPGA).
  • Figure 3: Unbalanced Mach-Zehnder Interferometer (uMZI) design.
  • Figure 4: Hardware subsystem timing statistics. $T_c$ of the laser source, $T_d$ of the delayed MZI, $T_r$ of the photodiode, and $T_s$ of the oscilloscope.
  • Figure 5: Voltage variance and QSCNR analysis: (a) The laser operating power $(mW)$ on x-axis and the voltage variance $\langle V^{2} \rangle$ of laser output on y-axis, and (b) The laser operating power in $mW$ on the x-axis, and the quantum signal to classical noise ratio ($QSCNR$) on the y-axis.
  • ...and 3 more figures