Realistic analysis of some randomized algorithms

  • Authors:
  • E. Bach

  • Affiliations:
  • Computer Sciences Department, University of Wisconsin, Madison, WI

  • Venue:
  • STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
  • Year:
  • 1987

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Abstract

Many problems such as primality testing can be solved efficiently using a source of independent, identically distributed random numbers. It is therefore customary in the theory of algorithms to assume the availability of such a source. However, probabilistic algorithms often work well in practice with pseudo-random numbers; the point of this paper is to offer a justification for this fact.The results below apply to sequences generated by iteratively applying functions of the form ƒ (&khgr;) = &agr;&khgr; + &bgr; (mod p) to a randomly chosen seed x, and estimate the probability that a predetermined number of trials of an algorithm will fail. In particular, the following bounds hold:For finding square roots modulo a prime p, a failure probability of &Ogr; (log p/√p).For testing p for primality, a failure probability of &Ogr; (p-1/4+&egr;), for any &egr;0.(In both cases, the number of trials is about 1/2 log p.) The analysis uses results of André Weil concerning the number of points on algebraic varieties over finite fields.