IEEE Photonics Journal (Jan 2022)

Extracting More Quantum Randomness With Non-Uniform Quantization

  • Bai-Xiang Ji,
  • Jian Li,
  • Qin Wang

DOI
https://doi.org/10.1109/jphot.2022.3199376
Journal volume & issue
Vol. 14, no. 4
pp. 1 – 6

Abstract

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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.

Keywords