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Extractors for a Constant Number of Polynomially Small Min-Entropy Independent Sources

To appear in STOC 2006.

This paper is about extracting randomness from independent sources.

Many applications in computer science require a source of true high quality random bits, yet such a source may not be available. In this work we show how to deterministically extract high quality randomness from several independent sources of low quality randomness.

It turns out that this task is equivalent to giving an explicit deterministic way to color the set [N]^c with M colors so that the coloring "looks random" in the following sense: for any large enough rectangle in the set, the number of points in the rectangle colored a particular color is about what you would expect for a random coloring. The goal is to maximize M, minimize c and minimize the size of the rectangles (a.k.a. the entropy of the sources) for which the extractor succeeds.

In this paper, we construct an extractor that can extract from a constant (c) number of independent sources of length n (N = 2^n), each of which have min-entropy that is polynomially small in n (say n^delta for some arbitrarily small constant delta). Previously the best known extractors for a constant number of independent sources required the sources to have min-entropy at least linear in n. Our extractor is built by composing previous constructions of strong seeded extractors in simple ways. We introduce a new technique to condense somewhere random sources that seems like a useful way to manipulate independent sources. Unlike other recent work for this problem, our main result does not rely on any results from additive number theory.

Using Bourgain's extractor (which does use results from additive number theory) as a black box, we show how to obtain a new extractor for 2 independent blockwise 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. and Raz's 3 source extractor to get dispersers/extractors with exponentially small error and linear output length where previously both were constant.
 


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