From affine to two-source extractors via approximate duality

Eli Ben-Sasson, Noga Ron-Zewi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We establish a new connection between affine and two-source extractors by presenting black-box constructions of two-source extractors for min-entropy rate below half from any affine extractor for min-entropy rate below half. Two such constructions are presented, and one of our constructions can reach arbitrarily small min-entropy rate assuming that the affine extractor has sufficiently good parameters. The first part of our analysis shows that our constructions are twosource dispersers which are weak (but nontrivial) kinds of two-source extractors, also known as "bipartite Ramsey graphs." To strengthen this result and obtain two-source extractors we introduce the approximate duality conjecture (ADC) and initiate its study. The ADC leads to a rather general result that can be used to convert a natural class of two-source dispersers-"low-rank dispersers"-into two-source extractors. More specifically, we first prove a special case of ADC that implies that the constructions mentioned above are two-source extractors with large (but nontrivial) constant error. In an attempt to reduce the error in our constructions we show that the polynomial Freiman-Ruzsa conjecture (PFR) in additive combinatorics implies a stronger "approximate duality" statement (and that this stronger statement also implies a weak but as-of-yet-unknown version of PFR). This stronger statement implies in turn that our constructions are two-source extractors with exponentially small error.

Original languageEnglish
Pages (from-to)1670-1697
Number of pages28
JournalSIAM Journal on Computing
Volume44
Issue number6
DOIs
StatePublished - 1 Jan 2015
Externally publishedYes

Keywords

  • Affine sources
  • Approximate duality
  • Discrepancy
  • Dispersers
  • Extractors
  • Independent sources
  • Polynomial Freiman-Ruzsa conjecture
  • Ramsey graphs

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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