LEBESGUE DENSITY AND $\prod _1^0$ CLASSES.

Analyzing the effective content of the Lebesgue density theorem played a crucial role in some recent developments in algorithmic randomness, namely, the solutions of the ML-covering and ML-cupping problems. Two new classes of reals emerged from this inquiry: the positive density points with respect...

Descripción completa

Detalles Bibliográficos
Publicado en:Journal of Symbolic Logic Vol. 81; no. 1; pp. 80 - 96
Autor principal: KHAN, MUSHFEQ
Formato: Artículo
Publicado: Cambridge University Press Mar2016
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=113600893&site=ehost-live
header:
  @attributes:
    shortDbName: hlh
    uiTerm: 113600893
    longDbName: Humanities International Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        00224812
        3TY
      jtl: Journal of Symbolic Logic
      issn: 00224812
      maglogo: N
    pubinfo:
      dt: Mar2016
      vid: 81
      iid: 1
      pid: 15979
      pub: Cambridge University Press
    artinfo:
      ui:
        113600893
        10.1017/jsl.2015.66
      ppf: 80
      ppct: 16
      formats:
      tig:
        atl: LEBESGUE DENSITY AND $\prod _1^0$ CLASSES.
      aug:
        au: KHAN, MUSHFEQ
        affil: DEPARTMENT OF MATHEMATICS UNIVERSITY OF HAWAII AT MANOA 2565 MCCARTHY MALL (KELLER HALL 401A) HONOLULU, HAWAII 96822, USA E-mail: khan@math.hawaii.edu
      su:
        Algorithmic randomness
        Mathematics theorems
        Algorithms
        Random effects model
        Computable functions
      sug:
        subj:
          Algorithmic randomness
          Mathematics theorems
          Algorithms
          Random effects model
          Computable functions
      keyword:
        03D32
        03D78
        03F60
        26E40
        effective analysis
      ab: Analyzing the effective content of the Lebesgue density theorem played a crucial role in some recent developments in algorithmic randomness, namely, the solutions of the ML-covering and ML-cupping problems. Two new classes of reals emerged from this inquiry: the positive density points with respect to effectively closed (or $\prod _1^0$) sets of reals, and a proper subclass, the density-one points. Bienvenu, Hölzl, Miller, and Nies have shown that the Martin-Löf random positive density points are exactly the ones that do not compute the halting problem. Treating this theorem as our starting point, we present several new results that shed light on how density, randomness, and computational strength interact.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: Y
      dt:
        @attributes:
          year: 2016
    holdings:
      @attributes:
        islocal: N