This paper shows that a quantum mechanical algorithm that can query information relating to multiple items of the database can search a database for a unique item satisfying a given condition, in a single query [a query is defined as any question to the database to which the database has to return a (yes/no answer]. A classical algorithm will be limited to the information theoretic bound of at least ${log}_{2}N$ queries, which it would achieve by using a binary search.This paper shows that a quantum mechanical algorithm that can query information relating to multiple items of the database can search a database for a unique item satisfying a given condition, in a single query [a query is defined as any question to the database to which the database has to return a (yes/no answer]. A classical algorithm will be limited to the information theoretic bound of at least ${log}_{2}N$ queries, which it would achieve by using a binary search.

arXiv:quant-ph/9706005Physical Review LettersDec 8, 1997432 citations

Quantum Search in Structured Database

Yuguo He, Jigui Sun

Lecture notes in computer scienceJan 1, 20053 citations

The Generalized Quantum Database Search Algorithm

Sándor Imre, F. Bal�zs

ComputingAug 26, 20048 citations

Complex Quantum Queries

Lov K. Grover

A quantum mechanical computer can search a database consisting of N items in O(sqrt(N)) elementary quantum queries (a query is defined as any question to the database to which a binary (YES/NO) answer is required; an elementary query is a query pertaining to only one of the N possible states). A classical computer would take at least O(N) elementary queries. This paper shows that a quantum mechanical algorithm that can query information relating to multiple states, can search the database in a single query. A classical algorithm will be limited to the information theoretic bound of at least O(log N)queries (which it would achieve by using a binary search). A similar result was recently independently obtained by Terhal & Smolin by a different method.A quantum mechanical computer can search a database consisting of N items in O(sqrt(N)) elementary quantum queries (a query is defined as any question to the database to which a binary (YES/NO) answer is required; an elementary query is a query pertaining to only one of the N possible states). A classical computer would take at least O(N) elementary queries. This paper shows that a quantum mechanical algorithm that can query information relating to multiple states, can search the database in a single query. A classical algorithm will be limited to the information theoretic bound of at least O(log N)queries (which it would achieve by using a binary search). A similar result was recently independently obtained by Terhal & Smolin by a different method.

Jun 3, 19970 citations

An efficient quantum search engine on unsorted database

Heping Hu, Yingyu Zhang, Zhengding Lu

We consider the problem of finding one or more desired items out of an unsorted database. Patel has shown that if the database permits quantum queries, then mere digitization is sufficient for efficient search for one desired item. The algorithm, called factorized quantum search algorithm, presented by him can locate the desired item in an unsorted database using $O(log_{4}N)$ queries to factorized oracles. But the algorithm requires that all the property values must be distinct from each other. In this paper, we discuss how to make a database satisfy the requirements, and present a quantum search engine based on the algorithm. Our goal is achieved by introducing auxiliary files for the property values that are not distinct, and converting every complex query request into a sequence of calls to factorized quantum search algorithm. The query complexity of our algorithm is $O(P*Q*M*log_{4}N)$ , where P is the number of the potential simple query requests in the complex query request, Q is the maximum number of calls to the factorized quantum search algorithm of the simple queries, M is the number of the auxiliary files for the property on which our algorithm are searching for desired items. This implies that to manage an unsorted database on an actual quantum computer is possible and efficient.We consider the problem of finding one or more desired items out of an unsorted database. Patel has shown that if the database permits quantum queries, then mere digitization is sufficient for efficient search for one desired item. The algorithm, called factorized quantum search algorithm, presented by him can locate the desired item in an unsorted database using $O(log_{4}N)$ queries to factorized oracles. But the algorithm requires that all the property values must be distinct from each other. In this paper, we discuss how to make a database satisfy the requirements, and present a quantum search engine based on the algorithm. Our goal is achieved by introducing auxiliary files for the property values that are not distinct, and converting every complex query request into a sequence of calls to factorized quantum search algorithm. The query complexity of our algorithm is $O(P*Q*M*log_{4}N)$, where P is the number of the potential simple query requests in the complex query request, Q is the maximum number of calls to the factorized quantum search algorithm of the simple queries, M is the number of the auxiliary files for the property on which our algorithm are searching for desired items. This implies that to manage an unsorted database on an actual quantum computer is possible and efficient.

arXiv:0904.3060Apr 20, 20090 citations

{log}_{2}N

queries, which it would achieve by using a binary search.

O(log_{4}N)

queries to factorized oracles. But the algorithm requires that all the property values must be distinct from each other. In this paper, we discuss how to make a database satisfy the requirements, and present a quantum search engine based on the algorithm. Our goal is achieved by introducing auxiliary files for the property values that are not distinct, and converting every complex query request into a sequence of calls to factorized quantum search algorithm. The query complexity of our algorithm is

O(P*Q*M*log_{4}N)

, where P is the number of the potential simple query requests in the complex query request, Q is the maximum number of calls to the factorized quantum search algorithm of the simple queries, M is the number of the auxiliary files for the property on which our algorithm are searching for desired items. This implies that to manage an unsorted database on an actual quantum computer is possible and efficient.