Deterministic Extraction from Weak Random Sources

Beschreibung

A deterministic extractor is a function that extracts almost perfect random bits from a weak random source. In this research monograph the author constructs deterministic extractors for several types of sources. A basic theme in this work is a methodology of recycling randomness which enables increasing the output length of deterministic extractors to near optimal length. The author's main work examines deterministic extractors for bit-fixing sources, deterministic extractors for affine sources and polynomial sources over large fields, and increasing the output length of zero-error dispersers. This work will be of interest to researchers and graduate students in combinatorics and theoretical computer science.
A deterministic extractor is a function that extracts almost perfect random bits from a weak random source. In this research monograph the author constructs deterministic extractors for several types of sources. A basic theme in this work is a methodology of recycling randomness which enables increasing the output length of deterministic extractors to near optimal length. The author's main work examines deterministic extractors for bit-fixing sources, deterministic extractors for affine sources and polynomial sources over large fields, and increasing the output length of zero-error dispersers. This work will be of interest to researchers and graduate students in combinatorics and theoretical computer science.
First complete treatment of the topic Introduces new results Results introduced will impact on various disciplines Includes supplementary material: sn.pub/extras

Autor*in

Ariel Gabizon

Themen in »Deterministic Extraction from Weak Random Sources«

Affine sources Derandomization Deterministic extractors Dispersers Randomness extractors Recycling randomness combinatorics

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From the reviews:

“This monograph is in the European Association for Theoretical Computer Science (EATCS) monograph series. It is an edited version of the author’s PhD thesis. … the book presents probability arguments and methods quite clearly, and in a way that readers can study them separately. Finally, the book contains two very useful appendices, one on probability methods and the other on concepts from algebraic geometry.” (Bruce Litow, ACM Computing Reviews, November, 2011)

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