True Random Number Generators on IQM Spark

TL;DR

This paper presents a comprehensive study of true random number generators on the IQM superconducting quantum computer, analyzing 105 circuit variants to evaluate their randomness quality using standard NIST test suites.

Contribution

First study to utilize the IQM superconducting architecture for quantum TRNGs, analyzing a large set of circuits on real hardware rather than simulations.

Findings

Generated 1 million bits per circuit variant

Performed extensive randomness testing with NIST standards

Compared quantum TRNG performance across multiple circuit types

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 Wroc{\l}aw 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.