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Quantum Algorithms for Intersection and Proximity Problems

  • Kunihiko Sadakane
  • Norito Sugawara
  • Takeshi Tokuyama
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2223)

Abstract

We discuss applications of quantum computation to geometric data processing. Especially, we give efficient algorithms for intersection problems and proximity problems. Our algorithms are based on Brassard et al.’s amplitude amplification method, and analogous to Buhrman et al.’s algorithm for element distinctness. Revealing these applications is useful for classifying geometric problems, and also emphasizing potential usefulness of quantum computation in geometric data processing. Thus, the results will promote research and development of quantum computers and algorithms.

Keywords

Voronoi Diagram Quantum Algorithm Target Data Quantum Model Identical Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Kunihiko Sadakane
    • 1
  • Norito Sugawara
    • 1
  • Takeshi Tokuyama
    • 1
  1. 1.Graduate School of Information SciencesTohoku UniversitySendaiJapan

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