2012/12/03 by Wolfgang Mauerer, Christopher Portmann, Mauerer, Wolfgang +3 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · #Complexity and Algorithms in Graphs #Computability, Logic, AI Algorithms #DNA and Biological Computing #FOS: Computer and information sciences #FOS: Physical sciences #Information Theory (cs.IT) #Mathematical Software (cs.MS) #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.1212.0520
openalex publication_date 2012/12/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Informally, an extractor delivers perfect randomness from a source that may be far away from the uniform distribution, yet contains some randomness. This task is a crucial ingredient of any attempt to produce perfectly random numbers---required, for instance, by cryptographic protocols, numerical simulations, or randomised computations. Trevisan's extractor raised considerable theoretical interest not only because of its data parsimony compared to other constructions, but particularly because it is secure against quantum adversaries, making it applicable to quantum key distribution. We discuss a modular, extensible and high-performance implementation of the construction based on various building blocks that can be flexibly combined to satisfy the requirements of a wide range of scenarios. Besides quantitatively analysing the properties of many combinations in practical settings, we improve previous theoretical proofs, and give explicit results for non-asymptotic cases. The self-contained description does not assume familiarity with extractors.