The complexity and distribution of hard problems

  • Authors:
  • D. W. Juedes;J. H. Lutz

  • Affiliations:
  • Dept. of Comput. Sci., Iowa State Univ., Ames, IA, USA;Dept. of Comput. Sci., Iowa State Univ., Ames, IA, USA

  • Venue:
  • SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
  • Year:
  • 1993

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Abstract

Measure-theoretic aspects of the /spl les//sub m//sup P/-reducibility structure of exponential time complexity classes E=DTIME(2/sup linear/) and E/sub 2/=DTIME(2/sup polynomial/) are investigated. Particular attention is given to the complexity (measured by the size of complexity cores) and distribution (abundance in the sense of measure) of languages that are /spl les//sub m//sup P/-hard for E and other complexity classes. Tight upper and lower bounds on the size of complexity cores of hard languages are derived. The upper bounds say that the /spl les//sub m//sup P/-hard languages for E are unusually simple in, the sense that they have smaller complexity cores than most languages in E. It follows that the /spl les//sub m//sup P/-complete languages for E form a measure 0 subset of E (and similarly in E/sub 2/). This latter fact is seen to be a special case of a more general theorem, namely, that every /spl les//sub m//sup P/-degree (e.g. the degree of all /spl les//sub m//sup P/-complete languages for NP) has measure 0 in E and in E/sub 2/.