Extracting More Quantum Randomness With Non-Uniform Quantization

• Published in: IEEE photonics journal 2022-08, Vol.14 (4), p.1-6
• Main Authors: Ji, Bai-Xiang, Li, Jian, Wang, Qin
• Format: Article
• Language: English
• Subjects: Analog to digital converters; Cryptography; Detectors; Elementary particle vacuum; Entropy; Fluctuations; Measurement; Min-entropy; Probability density function; Quantization (signal); Quantum random-number generation; Random numbers; Randomness; Sampling methods; Sequences
• ISSN: 1943-0655; 1943-0655; 1943-0647
• DOI: 10.1109/JPHOT.2022.3199376

Random numbers generated via quantum process is indeterministic, which are of essential to the cryptographic communication and the large-scale computer modeling. However, in realistic scenarios, classical noises can inevitably contaminate the raw sequences of a quantum randomness number generator (QRNG), and then compromise the security of the QRNG. Min-entropy is a useful approach that can quantify the randomness independent of side-information. To enhance the extractable randomness of the raw sequences arising from the QRNG, we propose a new method which exploits non-uniform quantization methods instead of uniform sampling methods and effectively enhances the extractable randomness from the QRNG at a high quantum-to-classical-noise ratio (QCNR). Given a QCNR as 50 dB and a 16-bit analog-to-digital converter (ADC), the worst-case conditional min-entropy of the non-uniform quantization scheme is improved by nearly 11% compared with that of the uniform sampling scheme.