Work

Efficient Randomness Extraction in Quantum Random Number Generators

Year: 2022

Type: conference-paper

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.

DOI: 10.5753/wquantum.2022.223591

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

Institution: University of Aveiro

Language: English

Topic: Quantum Information and Cryptography

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: Fundação para a Ciência e a Tecnologia, European Regional Development Fund

Awards: G1167214205, G1578237752, G2031848694, G2144570049, Instituto de Telecomunicações, G3850789590, G3891694003, G491858407, G6329845220, Geração de números primos habilitada por tecnologias quânticas para aplicações criptográficas

OpenAlex ID: W4313176008

FWCI: 0.553

Cites: 16

Cited by: 4

Related to: 10