Stream randomness extraction against quantum side information

Fuente: arXiv
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Auteurs principaux: Luan, Chun-Yang, Lie, Xiang-Jie, Cheng, Lin, Wang, Gang-Xi, Pan, Cheng-Kang, Zhang, Xiang, Zhang, Xingjian
Format: Preprint
Publié: 2026
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author Luan, Chun-Yang
Lie, Xiang-Jie
Cheng, Lin
Wang, Gang-Xi
Pan, Cheng-Kang
Zhang, Xiang
Zhang, Xingjian
author_facet Luan, Chun-Yang
Lie, Xiang-Jie
Cheng, Lin
Wang, Gang-Xi
Pan, Cheng-Kang
Zhang, Xiang
Zhang, Xingjian
contents Randomness extraction is indispensable for quantum random number generators, serving to eliminate bias and potential information leakage from raw measurement data. Conventional extractors operate in a block-wise fashion, requiring the complete accumulation of raw data before processing. To circumvent the latency and buffering overheads that hinder real-time random number generation, recent work introduced a stream-cipher implementation for the randomness extractor based on the Toeplitz matrix hashing. In this work, we generalize this stream-processing paradigm to the broader family of randomness extractors based on (almost dual) universal$_2$ random hashing. Specifically, we shift the computational burden from a time-consuming block-wise post-processing stage into an offline pre-processing stage that generates a pseudo-random mask. This allows the raw data to be processed by the mask on the fly using a simple bitwise exclusive-OR operation. Crucially, we prove that this stream implementation strictly preserves the security guarantees of the original block-wise protocols. We detail the transformation of three typical constructions -- based on standard Toeplitz, circulant, and modified Toeplitz matrices -- from block to stream implementations, and benchmark their practical performance using realistic quantum experimental data. We anticipate our framework will enhance the efficiency of real-time quantum cryptographic systems.
format Preprint
id arxiv_https___arxiv_org_abs_2605_09556
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Stream randomness extraction against quantum side information
Luan, Chun-Yang
Lie, Xiang-Jie
Cheng, Lin
Wang, Gang-Xi
Pan, Cheng-Kang
Zhang, Xiang
Zhang, Xingjian
Quantum Physics
Randomness extraction is indispensable for quantum random number generators, serving to eliminate bias and potential information leakage from raw measurement data. Conventional extractors operate in a block-wise fashion, requiring the complete accumulation of raw data before processing. To circumvent the latency and buffering overheads that hinder real-time random number generation, recent work introduced a stream-cipher implementation for the randomness extractor based on the Toeplitz matrix hashing. In this work, we generalize this stream-processing paradigm to the broader family of randomness extractors based on (almost dual) universal$_2$ random hashing. Specifically, we shift the computational burden from a time-consuming block-wise post-processing stage into an offline pre-processing stage that generates a pseudo-random mask. This allows the raw data to be processed by the mask on the fly using a simple bitwise exclusive-OR operation. Crucially, we prove that this stream implementation strictly preserves the security guarantees of the original block-wise protocols. We detail the transformation of three typical constructions -- based on standard Toeplitz, circulant, and modified Toeplitz matrices -- from block to stream implementations, and benchmark their practical performance using realistic quantum experimental data. We anticipate our framework will enhance the efficiency of real-time quantum cryptographic systems.
title Stream randomness extraction against quantum side information
topic Quantum Physics
url https://arxiv.org/abs/2605.09556