Three-Source Extractors for Polylogarithmic Min-Entropy

TL;DR

This paper constructs explicit three-source extractors for polylogarithmic min-entropy, significantly improving error bounds and advancing towards optimal randomness extraction from multiple weak sources.

Contribution

The paper introduces a nearly optimal three-source extractor with improved error bounds, advancing the construction of explicit extractors for weak random sources.

Findings

Constructed a three-source extractor for polylogarithmic min-entropy.

Improved error bound from 1/poly(n) to 2^{-k^{Ω(1)}}.

Works for one source with polylogarithmic min-entropy and another with two such sources.

Abstract

We continue the study of constructing explicit extractors for independent general weak random sources. The ultimate goal is to give a construction that matches what is given by the probabilistic method --- an extractor for two independent $n$-bit weak random sources with min-entropy as small as $\log n+O(1)$. Previously, the best known result in the two-source case is an extractor by Bourgain \cite{Bourgain05}, which works for min-entropy $0.49n$; and the best known result in the general case is an earlier work of the author \cite{Li13b}, which gives an extractor for a constant number of independent sources with min-entropy $\mathsf{polylog(n)}$. However, the constant in the construction of \cite{Li13b} depends on the hidden constant in the best known seeded extractor, and can be large; moreover the error in that construction is only $1/\mathsf{poly(n)}$. In this paper, we make two important improvements over the result in \cite{Li13b}. First, we construct an explicit extractor for \emph{three} independent sources on $n$ bits with min-entropy $k \geq \mathsf{polylog(n)}$. In fact, our extractor works for one independent source with poly-logarithmic min-entropy and another independent block source with two blocks each having poly-logarithmic min-entropy. Thus, our result is nearly optimal, and the next step would be to break the $0.49n$ barrier in two-source extractors. Second, we improve the error of the extractor from $1/\mathsf{poly(n)}$ to $2^{-k^{\Omega(1)}}$, which is almost optimal and crucial for cryptographic applications. Some of the techniques developed here may be of independent interests.