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True Random Number Generators on IQM Spark

Andrzej Gnatowski, Jarosław Rudy, Teodor Niżyński, Krzysztof Święcicki

TL;DR

The paper tackles the challenge of obtaining true randomness from quantum hardware by systematically evaluating TRNG circuits on the IQM Spark Odra5 QPU. It compares 16 circuit families (including 5 core designs C1–C5 and gate variants) across 105 subvariants, generating 1 million bits per configuration and subjecting the results to the full NIST SP 800-22 and SP 800-90B test suites. Key findings show native Rx/Ry gates outperform transpiled Hadamard implementations, parallel single-qubit circuits deliver strong randomness, and GHZ-based entanglement introduces a parity-dependent bias requiring hardware-aware design. The study demonstrates the importance of architectural specifics and provides a baseline for IQM hardware in QRNG research, while acknowledging limitations due to sample size and device calibration stability.

Abstract

Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On the other hand, True Random Number Generation (TRNG) offers true randomness. One way of obtaining such randomness are quantum systems, including quantum computers. As such the use of quantum computers for TRNG has received considerable attention in recent years. However, existing studies almost exclusively consider IBM quantum computers, often stop at using simulations and usually test only a handful of different TRNG quantum circuits. In this paper, we address those issues by presenting a study of TRNG circuits on Odra 5 a real-life quantum computer installed at Wrocław University of Science and Technology. It is also the first study to utilize the IQM superconducting architecture. Since Odra 5 is available on-premises it allows for much more comprehensive study of various TRNG circuits. In particular, we consider 5 types of TRNG circuits with 105 circuit subvariants in total. Each circuit is used to generate 1 million bits. We then perform an analysis of the quality of the obtained random sequences using the NIST SP 800-22 and NIST SP 800-90B test suites. We also provide a comprehensive review of existing literature on quantum computer-based TRNGs.

True Random Number Generators on IQM Spark

TL;DR

The paper tackles the challenge of obtaining true randomness from quantum hardware by systematically evaluating TRNG circuits on the IQM Spark Odra5 QPU. It compares 16 circuit families (including 5 core designs C1–C5 and gate variants) across 105 subvariants, generating 1 million bits per configuration and subjecting the results to the full NIST SP 800-22 and SP 800-90B test suites. Key findings show native Rx/Ry gates outperform transpiled Hadamard implementations, parallel single-qubit circuits deliver strong randomness, and GHZ-based entanglement introduces a parity-dependent bias requiring hardware-aware design. The study demonstrates the importance of architectural specifics and provides a baseline for IQM hardware in QRNG research, while acknowledging limitations due to sample size and device calibration stability.

Abstract

Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On the other hand, True Random Number Generation (TRNG) offers true randomness. One way of obtaining such randomness are quantum systems, including quantum computers. As such the use of quantum computers for TRNG has received considerable attention in recent years. However, existing studies almost exclusively consider IBM quantum computers, often stop at using simulations and usually test only a handful of different TRNG quantum circuits. In this paper, we address those issues by presenting a study of TRNG circuits on Odra 5 a real-life quantum computer installed at Wrocław University of Science and Technology. It is also the first study to utilize the IQM superconducting architecture. Since Odra 5 is available on-premises it allows for much more comprehensive study of various TRNG circuits. In particular, we consider 5 types of TRNG circuits with 105 circuit subvariants in total. Each circuit is used to generate 1 million bits. We then perform an analysis of the quality of the obtained random sequences using the NIST SP 800-22 and NIST SP 800-90B test suites. We also provide a comprehensive review of existing literature on quantum computer-based TRNGs.

Paper Structure

This paper contains 22 sections, 5 equations, 8 figures, 4 tables.

Table of Contents

  1. Introduction
  2. The challenge of true randomness
  3. The quantum promise and NISQ reality
  4. State of the field: fragmented and incomplete
  5. Contributions and structure of this paper
  6. Preliminaries
  7. Quantum computing
  8. Randomness testing
  9. Empirical tests
  10. NIST 22 test suite
  11. NIST 90B test suite
  12. Related work
  13. Methods
  14. Odra 5 quantum computer
  15. Quantum circuits
  16. ...and 7 more sections

Figures (8)

  • Figure 1: Topology of Odra 5
  • Figure 2: Circuits C1 (* is either $H$, $R_x(\frac{\pi}{2})$ or $R_y(\frac{\pi}{2})$ gate)
  • Figure 3: Circuits C2 (* is either $H$, $R_x(\frac{\pi}{2})$ or $R_y(\frac{\pi}{2})$ gate)
  • Figure 4: Example circuit C3 with GHZ state on all qubits (* is either $H$, $R_x(\frac{\pi}{2})$ or $R_y(\frac{\pi}{2})$ gate)
  • Figure 5: Circuits C4 (* is either $H$, $R_x(\frac{\pi}{2})$ or $R_y(\frac{\pi}{2})$ gate)
  • ...and 3 more figures