Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Chinese Physics Letters

Quantum Partial Searching Algorithm of a Database with Several Target Items

钟普查, 鲍皖苏, 魏云

Published Jan 1, 2009• 0 citations
OpenAlex

Abstract

Choi 和 Korepin [量信息处理 6 (2007 ) 243 ] 介绍了量有当每目标块包含目标项目的一样的数字时，能快速发现目标块的几个目标项目的一个数据库的部分搜索算法。实际上，在每目标块的目标项目的数字是任意的。瞄准这个盒子，我们给一个条件保证要表现的部分搜索算法和询问的数字的性能到要最小化的算法的神谕。另外，由进一步数字的计算，我们来到结论越多制服目标项目的分发，越 smaller 询问的数字。

Related papers

Quantum Partial Search of a Database with Several Target Items

Byung-Soo Choi, V. E. Korepin

arXiv:quant-ph/0608106•Quantum Information Processing•Aug 1, 2007•18 citations

Quantum partial search algorithm with smaller oracles for multiple target items

Dan Li, Ling Qian, Yuqian Zhou +1 more

Quantum Information Processing•Apr 27, 2022•3 citations

Quantum partial search for uneven distribution of multiple target items

Kun Zhang, V. E. Korepin

arXiv:1709.08230•Quantum Information Processing•Apr 28, 2018•12 citations

Quantum Partial Searching Algorithm of a Database with Several Target Items

Zhong Pu-Cha, Wan‐Su Bao, Wei-Yun Ma

Choi and Korepin [Quantum Information Processing 6(2007)243] presented a quantum partial search algorithm of a database with several target items which can find a target block quickly when each target block contains the same number of target items. Actually, the number of target items in each target block is arbitrary. Aiming at this case, we give a condition to guarantee performance of the partial search algorithm to be performed and the number of queries to oracle of the algorithm to be minimized. In addition, by further numerical computing we come to the conclusion that the more uniform the distribution of target items, the smaller the number of queries.

Chinese Physics Letters•Feb 1, 2009•1 citation

QUANTUM SEARCH ALGORITHMS

V. E. Korepin, YING XU

This article reviews recent progress in quantum database search algorithms. The subject is presented in a self-contained and pedagogical way. The problem of searching a large database (a Hilbert space) for a target item is performed by the famous Grover algorithm which locates the target item with high probability and a quadratic speed-up compared with the corresponding classical algorithm. If the database is partitioned into blocks and one is searching for the block containing the target item instead of the target item itself, then the problem is referred to as partial search. Partial search trades accuracy for speed and the most efficient version is the Grover–Radhakrishnan–Korepin (GRK) algorithm. The target block can be further partitioned into sub-blocks so that GRK's can be performed in a sequence called a hierarchy. We study the Grover search and GRK partial search in detail and prove that a GRK hierarchy is less efficient than a direct GRK partial search. Both the Grover search and the GRK partial search can be generalized to the case with several target items (or target blocks for a GRK). The GRK partial search algorithm can also be represented in terms of group theory.

International Journal of Modern Physics B•Dec 20, 2009•7 citations

Group Theoretical Formulation of a Quantum Partial Search Algorithm

V. E. Korepin, Brenno Carlini Vallilo

Searching and sorting are used as a subroutine in many important algorithms. Quantum algorithm can find a target item in a database faster than any classical algorithm. One can trade accuracy for speed and find a part of the database (a block) containing the target item even faster; this is a partial search. For example, an exact address of the target item is given by a sequence of many bits, but we need to know only some of them. More generally, a partial search considers the problem in which a database is separated into several blocks and we want to find a block with the target item, not the target item itself. In this paper, we reformulate a quantum partial search algorithm in terms of group theory.

arXiv:quant-ph/0609205•Progress of Theoretical Physics•Nov 1, 2006•14 citations
Choi 和 Korepin [量信息处理 6 (2007 ) 243 ] 介绍了量有当每目标块包含目标项目的一样的数字时，能快速发现目标块的几个目标项目的一个数据库的部分搜索算法。实际上，在每目标块的目标项目的数字是任意的。瞄准这个盒子，我们给一个条件保证要表现的部分搜索算法和询问的数字的性能到要最小化的算法的神谕。另外，由进一步数字的计算，我们来到结论越多制服目标项目的分发，越 smaller 询问的数字。
Choi and Korepin [Quantum Information Processing 6(2007)243] presented a quantum partial search algorithm of a database with several target items which can find a target block quickly when each target block contains the same number of target items. Actually, the number of target items in each target block is arbitrary. Aiming at this case, we give a condition to guarantee performance of the partial search algorithm to be performed and the number of queries to oracle of the algorithm to be minimized. In addition, by further numerical computing we come to the conclusion that the more uniform the distribution of target items, the smaller the number of queries.
This article reviews recent progress in quantum database search algorithms. The subject is presented in a self-contained and pedagogical way. The problem of searching a large database (a Hilbert space) for a target item is performed by the famous Grover algorithm which locates the target item with high probability and a quadratic speed-up compared with the corresponding classical algorithm. If the database is partitioned into blocks and one is searching for the block containing the target item instead of the target item itself, then the problem is referred to as partial search. Partial search trades accuracy for speed and the most efficient version is the Grover–Radhakrishnan–Korepin (GRK) algorithm. The target block can be further partitioned into sub-blocks so that GRK's can be performed in a sequence called a hierarchy. We study the Grover search and GRK partial search in detail and prove that a GRK hierarchy is less efficient than a direct GRK partial search. Both the Grover search and the GRK partial search can be generalized to the case with several target items (or target blocks for a GRK). The GRK partial search algorithm can also be represented in terms of group theory.
Searching and sorting are used as a subroutine in many important algorithms. Quantum algorithm can find a target item in a database faster than any classical algorithm. One can trade accuracy for speed and find a part of the database (a block) containing the target item even faster; this is a partial search. For example, an exact address of the target item is given by a sequence of many bits, but we need to know only some of them. More generally, a partial search considers the problem in which a database is separated into several blocks and we want to find a block with the target item, not the target item itself. In this paper, we reformulate a quantum partial search algorithm in terms of group theory.