• DocumentCode
    2356976
  • Title

    Measure on small complexity classes, with applications for BPP

  • Author

    Allender, Eric ; Strauss, Martin

  • Author_Institution
    Dept. of Comput. Sci., Rutgers Univ., New Brunswick, NJ, USA
  • fYear
    1994
  • fDate
    20-22 Nov 1994
  • Firstpage
    807
  • Lastpage
    818
  • Abstract
    We present a notion of resource-bounded measure for P and other subexponential-time classes. This generalization is based on Lutz´s notion of measure, but overcomes the limitations that cause Lutz´s definitions to apply only to classes at least as large as E. We present many of the basic properties of this measure, and use it to explore the class of sets that are hard for BPP. Bennett and Gill showed that almost all sets are hard for BPP; Lutz improved this from Lebesgue measure to measure on ESPACE. We use our measure to improve this still further, showing that for all ε>0, almost every set in Eε is hard for BPP, where Eε=∪δ<εDTIME(2(n δ)), which is the best that can be achieved without showing that BPP is properly contained in E. A number of related results are also obtained in this way
  • Keywords
    computational complexity; BPP; class of sets; resource-bounded measure; resource-bounded measure theory; small complexity classes; subexponential-time classes; Application software; Complexity theory; Computer science; Density measurement; Mathematics; Polynomials; Power measurement; Q measurement; Robustness; Time measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Foundations of Computer Science, 1994 Proceedings., 35th Annual Symposium on
  • Conference_Location
    Santa Fe, NM
  • Print_ISBN
    0-8186-6580-7
  • Type

    conf

  • DOI
    10.1109/SFCS.1994.365713
  • Filename
    365713