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Quantum Sampling for Balanced Allocations

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Part of the book series:Lecture Notes in Computer Science ((LNCS,volume 2697))

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Abstract

It is known that the original Grover Search (GS) can be modified to use a general value for the phaseθ of the diffusion transform. Then, if the number of answers is relatively large, this modified GS can find one of the answers with probability one in a single iteration. However, such a quick and error-free GS can only be possible if we can initially adjust the value ofθ correctly against the number of answers, and this seems very hard in usual occasions. A natural question now arises: Can we enjoy a merit even if GS is used without such an adjustment? In this paper, we give a positive answer using the balls-and-bins game in which the random sampling of bins is replaced by the quantum sampling, i.e., a single round of modified GS. It is shown that by using the quantum sampling: (i) The maximum load can be improved quadratically for the static model of the game and this improvement is optimal. (ii) That is also improved toO(1) for the continuous model if we have a certain knowledge about the total number of balls in the bins after the system becomes stable.

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Author information

Authors and Affiliations

  1. Imai Quantum Computation and Information Project, ERATO, Japan Sci. and Tech. Corp., 406, Iseya-cho, Kamigyo-ku, Kyoto, 602-0873, Japan

    Kazuo Iwama, Akinori Kawachi & Shigeru Yamashita

  2. Graduate School of Informatics, Kyoto University Yoshida Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Kazuo Iwama & Akinori Kawachi

Authors
  1. Kazuo Iwama

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  2. Akinori Kawachi

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  3. Shigeru Yamashita

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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at Austin, One University Station, C0500, Austin, TX, 78712, USA

    Tandy Warnow

  2. Department of Computer Science, Montana State University, EPS 357, Bozeman, MT, 59717, USA

    Binhai Zhu

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© 2003 Springer-Verlag Berlin Heidelberg

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Iwama, K., Kawachi, A., Yamashita, S. (2003). Quantum Sampling for Balanced Allocations. In: Warnow, T., Zhu, B. (eds) Computing and Combinatorics. COCOON 2003. Lecture Notes in Computer Science, vol 2697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45071-8_32

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