An introduction to randomness extractors
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
Extractors and lower bounds for locally samplable sources
APPROX'11/RANDOM'11 Proceedings of the 14th international workshop and 15th international conference on Approximation, randomization, and combinatorial optimization: algorithms and techniques
Extractors and Lower Bounds for Locally Samplable Sources
ACM Transactions on Computation Theory (TOCT)
Improving the Hadamard extractor
Theoretical Computer Science
| Hi-index | 0.00 |
We study the problem of constructing affine extractors over $\GF(2)$. Previously the only known construction that can handle sources with arbitrarily linear entropy is due to Bourgain (and a slight modification by Yehudayoff), which makes extensive use of complicated inequality manipulations and relies on a careful choice of a polynomial. In this paper we give a new and conceptually much cleaner construction of affine extractors for linear entropy sources that outputs a constant fractionof the entropy with exponentially small error. This matches theprevious best result of Bourgain. The extractor can be pushed tohandle affine sources with entropy $n/\sqrt{\log n \logn}$. This slightly improves Bourgain's result andmatches the recent result of Yehudayoff. We also give a zero-error disperser for affine sources with entropy $n/\sqrt {\log n}$that outputs $n^{\Omega(1)}$ bits. This improves previousconstructions of affine dispersers that output more than 1 bit. In contrast to Bourgain's construction, our construction mainly uses extractor machinery and basic properties of polynomials. Some of our techniques may be of independent interest.