Efficient Randomness Extraction in Quantum Random Number Generators

Author:

Ferreira Maurício J.,Silva Nuno A.,Muga Nelson J.

Abstract

Randomness extraction algorithms play an essential role in Quantum Random Number Generators (QRNGs), where they are used to suppress unwanted classical noise and distill true randomness from their biased output. By employing the SHA-512 hash function and Toeplitz matrix multiplication, we analyse two suitable constructions based on different principles and reach postprocessing rates of 8.69 Mbps and 3.68 Mbps, respectively. Finally, we develop a length-compatible Toeplitz-hashing algorithm able to achieve rates of 143.29 Mbps in a parallelized GPU implementation.

Publisher

Sociedade Brasileira de Computação

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Probable Prime Generation from a Quantum Randomness Source;2023 23rd International Conference on Transparent Optical Networks (ICTON);2023-07-02

2. A Network Server for Distributing Quantum Random Numbers;2023 23rd International Conference on Transparent Optical Networks (ICTON);2023-07-02

3. Efficiency improvement of photon arrival time based quantum random number generator with hashing;2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI);2023-05-23

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