Deep $\Pi^0_1$ Classes
Abstract
A set of infinite binary sequences is negligible if there is no partial probabilistic algorithm that produces an element of this set with positive probability. The study of negligibility is of particular interest in the context of classes. In this paper, we introduce the notion of depth for classes, which is a stronger form of negligibility. Whereas a negligible class has the property that one cannot probabilistically compute a member of with positive probability, a deep class has the property that one cannot probabilistically compute an initial segment of a member of with high probability. That is, the probability of computing a length initial segment of a deep class converges to 0 effectively in . We prove a number of basic results about depth, negligibility, and a variant of negligibility that we call -negligibility. We also provide a number of examples of deep classes that occur naturally in computability theory and algorithmic randomness. We also study deep classes in the context of mass problems, we examine the relationship between deep classes and certain lowness notions in algorithmic randomness, and establish a relationship between members of deep classes and the amount of mutual information with Chaitin's .
Cite
@article{arxiv.1403.0450,
title = {Deep $\Pi^0_1$ Classes},
author = {Laurent Bienvenu and Christopher P. Porter},
journal= {arXiv preprint arXiv:1403.0450},
year = {2017}
}