Barmpalias, George and LewisPye, Andrew (2017) Optimal redundancy in computations from random oracles. Journal of Computer and System Sciences. ISSN 00220000

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Abstract
It is a classic result in algorithmic information theory that every infinite binary sequence is computable from an infinite binary sequence which is random in the sense of MartinLöf. Proved independently by Kuˇcera [Kuˇc85] and Gács [Gác86], this result answered a question by Charles Bennett and has seen numerous applications in the last 30 years. The optimal redundancy in such a coding process has, however, remained unknown. If the computation of the first n bits of a sequence requires n+g(n) bits of the random oracle, then g is the redundancy of the computation. Kuˇcera implicitly achieved redundancy n log n while Gács used a more elaborate blockcoding procedure which achieved redundancy √n log n. Merkle and Mihailovi´c [MM04] provided a different presentation of Gács’ approach, without improving his redundancy bound. In this paper we devise a new coding method that achieves optimal logarithmic redundancy. For any computable nondecreasing function g such that Pi 2−g(i) is bounded we show that there is a coding process that codes any given infinite binary sequence into a MartinLöf random infinite binary sequence with redundancy g. This redundancy bound is exponentially smaller than the previous bound of √n log n and is known to be the best possible by recent work [BLPT16], where it was shown that if Pi 2−g(i) diverges then there exists an infinite binary sequence X which cannot be computed by any MartinLöf random infinite binary sequence with redundancy g. It follows that redundancy ǫ · log n in computation from a random oracle is possible for every infinite binary sequence, if and only if ǫ > 1.
Item Type:  Article 

Official URL:  https://www.journals.elsevier.com/journalofcompu... 
Additional Information:  © 2017 Elsevier Inc. 
Divisions:  Mathematics 
Subjects:  Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science 
Date Deposited:  26 Jun 2017 14:46 
Last Modified:  20 Oct 2021 03:24 
URI:  http://eprints.lse.ac.uk/id/eprint/82358 
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