Extractors for Near Logarithmic Min-Entropy

Gil Cohen, Leonard J. Schulman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations


The main contribution of this work is an explicit construction of extractors for near logarithmic min-entropy. For any δ > 0 we construct an extractor for O(1/δ) n-bit sources with min-entropy (logn)1+δ. This is most interesting when δ is set to a small constant, though the result also yields an extractor for O(log logn) sources with logarithmic min-entropy. Prior to this work, the best explicit extractor in terms of supporting least-possible min-entropy, due to Li (FOCS'15), requires min-entropy (logn)2+δ from its O(1/δ) sources. Further, all current techniques for constructing multi-source extractors 'break' below min-entropy (log n)2. In fact, existing techniques do not provide even a disperser for o(log n) sources each with min-entropy (log n)1.99. Apart from being a natural problem, supporting logarithmic min-entropy has applications to combinatorics. A two-source disperser, let alone an extractor, for min-entropy O(log n) induces a (log, nO(1))-Ramsey graph on n vertices. Thus, constructing such dispersers would be a significant step towards constructively matching Erds' proof for the existence of (2log n)-Ramsey graphs on n vertices. Our construction does not rely on the sophisticated primitives that were key to the substantial recent progress on multi-source extractors, such as non-malleable extractors, correlation breakers, the lightest-bin condenser, or extractors for non-oblivious bit-fixing sources, although some of these primitives can be combined with our construction so to improve the output length and the error guarantee. Instead, at the heart of our construction is a new primitive called an independence-preserving merger. The construction of the latter builds on the alternating extraction technique.

Original languageEnglish (US)
Title of host publicationProceedings - 57th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2016
PublisherIEEE Computer Society
Number of pages10
ISBN (Electronic)9781509039333
StatePublished - Dec 14 2016
Event57th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2016 - New Brunswick, United States
Duration: Oct 9 2016Oct 11 2016

Publication series

NameProceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
ISSN (Print)0272-5428


Other57th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2016
Country/TerritoryUnited States
CityNew Brunswick

All Science Journal Classification (ASJC) codes

  • General Computer Science


  • Correlation breakers
  • Extractors
  • Independence-preserving mergers


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