Quantum search on bounded-error inputs

  • Authors:
  • Peter Høyer;Michele Mosca;Ronald De Wolf

  • Affiliations:
  • Dept. of Computer Science, Univ. of Calgary, Alberta, Canada;Dept. of Combinatorics & Optimization, Univ. of Waterloo, Ontario, Canada;CWI, Amsterdam, The Netherlands

  • Venue:
  • ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
  • Year:
  • 2003

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Abstract

Suppose we have n algorithms, quantum or classical, each computing some bit-value with bounded error probability. We describe a quantum algorithm that uses O(√n) repetitions of the base algorithms and with high probability finds the index of a 1-bit among these n bits (if there is such an index). This shows that it is not necessary to first significantly reduce the error probability in the base algorithms to O(1/poly(n)) (which would require O(√n log n) repetitions in total). Our technique is a recursive interleaving of amplitude amplification and error-reduction, and may be of more general interest. Essentially, it shows that quantum amplitude amplification can be made to work also with a bounded-error verifier. As a corollary we obtain optimal quantum upper bounds of O(√N) queries for all constant-depth AND-OR trees on N variables, improving upon earlier upper bounds of O(√Npolylog(N)).