Title :
Symmetry of Information and Bounds on Nonuniform Randomness Extraction via Kolmogorov Extractors
Author_Institution :
Towson Univ., Baltimore, MD, USA
Abstract :
We prove a strong Symmetry of Information relation for random strings (in the sense of Kolmogorov complexity) and establish tight bounds on the amount on nonuniformity that is necessary for extracting a string with randomness rate 1 from a single source of randomness. More precisely, as instantiations of more general results, we show: · For all n-bit random strings x and y, x is random conditioned by y if and only if y is random conditioned by x; · While O(1) amount of advice regarding the source is not enough for extracting a string with randomness rate 1 from a source string with constant random rate, ω(1) amount of advice is. The proofs use Kolmogorov extractors as the main technical device.
Keywords :
computational complexity; Kolmogorov complexity; Kolmogorov extractors; information relation symmetry; nonuniform randomness extraction; random strings; randomness rate; Complexity theory; Data mining; Generators; Information theory; Polynomials; Probabilistic logic; Turing machines; Kolmogorov extractors; Symmetry of information; random strings; randomness extraction;
Conference_Titel :
Computational Complexity (CCC), 2011 IEEE 26th Annual Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4577-0179-5
Electronic_ISBN :
1093-0159
DOI :
10.1109/CCC.2011.21