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.
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Kunihiko SADAKANE, Norito SUGAWARA, Takeshi TOKUYAMA, "Quantum Algorithms for Intersection and Proximity Problems" in IEICE TRANSACTIONS on Fundamentals,
vol. E86-A, no. 5, pp. 1113-1119, May 2003, doi: .
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.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e86-a_5_1113/_p
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@ARTICLE{e86-a_5_1113,
author={Kunihiko SADAKANE, Norito SUGAWARA, Takeshi TOKUYAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Quantum Algorithms for Intersection and Proximity Problems},
year={2003},
volume={E86-A},
number={5},
pages={1113-1119},
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={},
doi={},
ISSN={},
month={May},}
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TY - JOUR
TI - Quantum Algorithms for Intersection and Proximity Problems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1113
EP - 1119
AU - Kunihiko SADAKANE
AU - Norito SUGAWARA
AU - Takeshi TOKUYAMA
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E86-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 2003
AB - 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.
ER -