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Extractors for a constant number of polynomially small min-entropy independent sources

60

Citations

30

References

2006

Year

Anup Rao

Unknown Venue

Abstract

We consider the problem of randomness extraction from independent sources. We construct an extractor that can extract from a constant number of independent sources of length n, each of which have min-entropy nγ for an arbitrarily small constant γ > 0. Our extractor is obtained by composing seeded extractors in simple ways. We introduce a new technique to condense independent somewhere-random sources which looks like a useful way to manipulate independent sources. Our techniques are different from those used in recent work [1, 2, 16, 5] for this problem in the sense that they do not rely on any results from additive number theory.Using Bourgain's extractor [5] as a black box, we obtain a new extractor for 2 independent block-sources with few blocks, even when the min-entropy is as small as polylog(n). We also show how to modify the 2 source disperser for linear min-entropy of Barak et al. [2] and the 3 source extractor of Raz [16] to get dispersers/extractors with exponentially small error and linear output length where previously both were constant.In terms of Ramsey Hypergraphs, for every constant 1> γ >0 our construction gives a family of explicit O(1/γ)-uniform hypergraphs on N vertices that avoid cliques and independent sets of size 2(log N)γ.

References

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