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Journal of Discrete Mathematical Sciences and Cryptography cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

Entropy diagnostics for cryptographic key material from random circuit sampling

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pp. 1023–1032Vol. 29Issue 2-BFebruary 2026DOI: 10.47974/JDMSC-2641 Crossmark XML
Received:
07 May 2025
Published Online:
18 Feb 2026
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-2641
Pages:
1023–1032

Abstract

Random Circuit Sampling (RCS) has emerged as a leading paradigm for demonstrating quantum advantage. Beyond computational complexity, RCS provides a high-dimensional, chaotic probability distribution whose structure is characteristic of random unitary dynamics; here, we study its entropy properties in an ideal statevector baseline intended for later hardware validation. In this work, we present a reproducible validation framework for certifying cryptographic keys using a 12-qubit RCS ensemble (N = 4096 “ states” ) within an ideal quantum simulation framework. Unlike standard Quantum Random Number Generators (QRNGs), which often rely on single-qubit optics, our protocol utilises multi-qubit entanglement to ensure nonlocality. We quantify the security of the system using a dual-metric approach: basis-dependent Min-Entropy (H∞ ≈ 9.05 “ bits” ) for cryptographic extractability, and basis-independent Subsystem Von Neumann Entropy (S ≈ 3.96 bits) for quantum certification. We further demonstrate a privacy-amplification pipeline that uses a frequency-preserving, endian-corrected SHA-3 extraction to produce a 256-bit secure key (candidate key material). This study provides a transparent methodological bridge between the theoretical “Quantum Supremacy” regime and practical cryptographic key generation.

Keywords

Subject Classifications

11T71

References

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