Cited by 256Computability, Logic, AI AlgorithmsMathematical Approximation and IntegrationCoding theory and cryptography

Generating quasi-random sequences from semi-random sources

Open access
Santha, Miklos, Vazirani, Umesh V.·1986·Journal of Computer and System Sciences

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Registry

Crossref · 10.1016/0022-0000(86)90044-9

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  • Any Santha-Vazirani weak source with ε < 0.058 can be amplified into arbitrarily free random bits in a self-testing way using a two-party chained Bell inequality and requiring only no-signalling.

    “Using a two-party chained Bell inequality, 71,72 they showed that any Santha -Vazirani weak sources 73 (de fi ned in Methods), with ϵ o 0.058, can be ampli fi ed into arbitrarily free random bits in a self-testing way by requiring only no-signalling.”

    From Quantum random number generation (2016) · cites this paper as [73]

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References 19 · Cited by 256

Authors
Santha, M., & Vazirani, U. V.
Affiliations
University of California, Berkeley (US)
Venue
Journal of Computer and System Sciences
Publisher
Elsevier BV
Published
1986-08
Volume
33
Issue
1
Pages
75-87
ISSN
0022-0000 (ISSN-L)
OpenAlex
W1977568210
Cited by
256
References
19
Citations by year
2026: 2 · 2025: 3 · 2024: 8 · 2023: 8 · 2022: 2 · 2021: 2 · 2020: 7 · 2019: 4 · 2018: 7 · 2017: 10 · 2016: 13 · 2015: 14 · 2014: 8 · 2013: 14 · 2012: 14
FWCI
3.34
Type
journal article
Language
en
Open access
Locations
Journal of Computer and System Sciences (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
  • Physical Sciences › Mathematics › Numerical Analysis › Mathematical Approximation and Integration
  • Physical Sciences › Computer Science › Artificial Intelligence › Coding theory and cryptography
Keywords
quasi-random sequences, randomness extraction, pseudorandom number generators, stochastic simulation

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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