English

Deterministic Randomness Extraction from Generalized and Distributed Santha-Vazirani Sources

Computational Complexity 2014-12-23 v1 Information Theory math.IT

Abstract

A Santha-Vazirani (SV) source is a sequence of random bits where the conditional distribution of each bit, given the previous bits, can be partially controlled by an adversary. Santha and Vazirani show that deterministic randomness extraction from these sources is impossible. In this paper, we study the generalization of SV sources for non-binary sequences. We show that unlike the binary case, deterministic randomness extraction in the generalized case is sometimes possible. We present a necessary condition and a sufficient condition for the possibility of deterministic randomness extraction. These two conditions coincide in "non-degenerate" cases. Next, we turn to a distributed setting. In this setting the SV source consists of a random sequence of pairs (a1,b1),(a2,b2),(a_1, b_1), (a_2, b_2), \ldots distributed between two parties, where the first party receives aia_i's and the second one receives bib_i's. The goal of the two parties is to extract common randomness without communication. Using the notion of maximal correlation, we prove a necessary condition and a sufficient condition for the possibility of common randomness extraction from these sources. Based on these two conditions, the problem of common randomness extraction essentially reduces to the problem of randomness extraction from (non-distributed) SV sources. This result generalizes results of G\'acs and K\"orner, and Witsenhausen about common randomness extraction from i.i.d. sources to adversarial sources.

Cite

@article{arxiv.1412.6641,
  title  = {Deterministic Randomness Extraction from Generalized and Distributed Santha-Vazirani Sources},
  author = {Salman Beigi and Omid Etesami and Amin Gohari},
  journal= {arXiv preprint arXiv:1412.6641},
  year   = {2014}
}
R2 v1 2026-06-22T07:39:14.598Z