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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.
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- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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- The goal of the ordered search problem is to find a particular item in an ordered list of n items.
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