AI Insight
This study presents novel parameterized quantum random number generator (QRNG) architectures designed for superconducting quantum hardware, evaluated using IBM noisy simulators. The proposed circuits leverage parameterized quantum gates to generate random bit sequences, and their statistical quality is assessed through the NIST SP 800-22 test suite, a standard benchmark for randomness validation. The results demonstrate that certain parameterized circuit architectures can produce outputs that satisfy multiple NIST statistical tests even under realistic noise conditions characteristic of current superconducting quantum devices.
Why it matters
High-quality random number generation is critical for cryptography, secure communications, and scientific simulations, and quantum hardware offers a physically grounded source of randomness that classical systems cannot replicate. This work provides practical design guidelines for implementing QRNGs on near-term superconducting quantum processors, advancing the deployment of quantum-enhanced security tools.