COARSE REDUCIBILITY AND ALGORITHMIC RANDOMNESS.

A coarse description of a set A ⊆ ω is a set D ⊆ ω such that the symmetric difference of A and D has asymptotic density 0. We study the extent to which noncomputable information can be effectively recovered from all coarse descriptions of a given set A, especially when A is effectively random in som...

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Publicado en:Journal of Symbolic Logic Vol. 81; no. 3; pp. 1028 - 1047
Autores principales: HIRSCHFELDT, DENIS R., JOCKUSCH, CARL G., KUYPER, RUTGER, SCHUPP, PAUL E.
Formato: Artículo
Publicado: Cambridge University Press Sep2016
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2016
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        atl: COARSE REDUCIBILITY AND ALGORITHMIC RANDOMNESS.
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        au:
          HIRSCHFELDT, DENIS R.
          JOCKUSCH, CARL G.
          KUYPER, RUTGER
          SCHUPP, PAUL E.
        affil:
          DEPARTMENT OF MATHEMATICS UNIVERSITY OF CHICAGO CHICAGO, IL, USA.
          DEPARTMENT OF MATHEMATICS UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN CHAMPAIGN, IL, USA
          DEPARTMENT OF MATHEMATICS UNIVERSITY OF WISCONSIN–MADISON MADISON, WI, USA
      su:
        Algorithmic randomness
        Compact spaces (Topology)
        Random sets
        Unsolvability (Mathematical logic)
        Computable functions
      sug:
        subj:
          Algorithmic randomness
          Compact spaces (Topology)
          Random sets
          Unsolvability (Mathematical logic)
          Computable functions
      keyword:
        03D32
        algorithmic randomness
        Coarse reducibility
        K-triviality
        Primary 03D30
        Secondary 03D28
      ab: A coarse description of a set A ⊆ ω is a set D ⊆ ω such that the symmetric difference of A and D has asymptotic density 0. We study the extent to which noncomputable information can be effectively recovered from all coarse descriptions of a given set A, especially when A is effectively random in some sense. We show that if A is 1-random and B is computable from every coarse description D of A, then B is K-trivial, which implies that if A is in fact weakly 2-random then B is computable. Our main tool is a kind of compactness theorem for cone-avoiding descriptions, which also allows us to prove the same result for 1-genericity in place of weak 2-randomness. In the other direction, we show that if $A \le _{{\rm{T}}} \emptyset {\rm{'}}$ is a 1-random set, then there is a noncomputable c.e. set computable from every coarse description of A, but that not all K-trivial sets are computable from every coarse description of some 1-random set. We study both uniform and nonuniform notions of coarse reducibility. A set Y is uniformly coarsely reducible to X if there is a Turing functional Φ such that if D is a coarse description of X, then ΦD is a coarse description of Y. A set B is nonuniformly coarsely reducible to A if every coarse description of A computes a coarse description of B. We show that a certain natural embedding of the Turing degrees into the coarse degrees (both uniform and nonuniform) is not surjective. We also show that if two sets are mutually weakly 3-random, then their coarse degrees form a minimal pair, in both the uniform and nonuniform cases, but that the same is not true of every pair of relatively 2-random sets, at least in the nonuniform coarse degrees.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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