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Open Quantum Systems Decoherence Quantum Machine Learning

Optimal quantum adversary lower bounds for ordered search

arXiv
Authors: Andrew M. Childs, Troy Lee

Year

2007

Paper ID

49272

Status

Preprint

Abstract Read

~2 min

Abstract Words

114

Citations

N/A

Abstract

The goal of the ordered search problem is to find a particular item in an ordered list of n items. Using the adversary method, Hoyer, Neerbek, and Shi proved a quantum lower bound for this problem of (1/pi) ln n + Theta(1). Here, we find the exact value of the best possible quantum adversary lower bound for a symmetrized version of ordered search (whose query complexity differs from that of the original problem by at most 1). Thus we show that the best lower bound for ordered search that can be proved by the adversary method is (1/pi) ln n + O(1). Furthermore, we show that this remains true for the generalized adversary method allowing negative weights.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2007 reference point for readers tracking recent quantum research.
  • The goal of the ordered search problem is to find a particular item in an ordered list of n items.

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