Possibilities and impossibilities in Kolmogorov complexity extraction
Computational Complexity
2012-06-19 v2
Abstract
Randomness extraction is the process of constructing a source of randomness of high quality from one or several sources of randomness of lower quality. The problem can be modeled using probability distributions and min-entropy to measure their quality and also by using individual strings and Kolmogorov complexity to measure their quality. Complexity theorists are more familiar with the first approach. In this paper we survey the second approach. We present the connection between extractors and Kolmogorov extractors and the basic positive and negative results concerning Kolmogorov complexity extraction.
Keywords
Cite
@article{arxiv.1104.0872,
title = {Possibilities and impossibilities in Kolmogorov complexity extraction},
author = {Marius Zimand},
journal= {arXiv preprint arXiv:1104.0872},
year = {2012}
}
Comments
Revised form of survey paper published in SIGACT News, Dec. 2010. A few corrections and references have been added