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Asymptotic density, immunity and randomness

Authors: Eric P. Astor;

Asymptotic density, immunity and randomness

Abstract

Abstract In 2012, inspired by developments in group theory and complexity, Jockusch and Schupp introduced generic computability, capturing the idea that an algorithm might work correctly except for a vanishing fraction of cases. However, we observe that their definition of a negligible set is not computably invariant (and thus not well-defined on the 1-degrees), resulting in some failures of intuition and a break with standard expectations in computability theory. To strengthen their approach, we introduce a new notion of intrinsic asymptotic density, with rich relations to both randomness and classical computability theory. We then apply these ideas to propose alternative foundations for further development in (intrinsic) generic computability. Toward these goals, we classify intrinsic density 0 as a new immunity property, specifying its position in the standard hierarchy from immune to cohesive for both general and [Formula: see text] sets, and identify intrinsic density [Formula: see text] as the stochasticity corresponding to permutation randomness. We also prove that Rice’s Theorem extends to all intrinsic variations of generic computability, demonstrating in particular that no such notion considers [Formula: see text] to be “computable”.

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Keywords

Recursively (computably) enumerable sets and degrees, Rice's theorem, Other Turing degree structures, generic computability, Mathematics - Logic, immunity, intrinsic density, Algorithmic randomness and dimension, FOS: Mathematics, Logic (math.LO), asymptotic density

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Average
Green
bronze