Bounds for Error Reduction with Few Quantum Queries

We consider the quantum database search problem, where we are given a function f: [N] → 0,1, and are required to return an x ∈ [N] (a target address) such that f(x)=1. Recently, Grover [G05] showed that there is an algorithm that after making one quantum query to the database, returns an X ∈ [N] (a...

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Published inApproximation, Randomization and Combinatorial Optimization. Algorithms and Techniques pp. 245 - 256
Main Authors Chakraborty, Sourav, Radhakrishnan, Jaikumar, Raghunathan, Nandakumar
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN9783540282396
3540282394
ISSN0302-9743
1611-3349
DOI10.1007/11538462_21

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Abstract We consider the quantum database search problem, where we are given a function f: [N] → 0,1, and are required to return an x ∈ [N] (a target address) such that f(x)=1. Recently, Grover [G05] showed that there is an algorithm that after making one quantum query to the database, returns an X ∈ [N] (a random variable) such that $$ \Pr[f(X)=0] = \epsilon^3,$$ where ε = |f− − 1(0)|/N. Using the same idea, Grover derived a t-query quantum algorithm (for infinitely many t) that errs with probability only ε2 t + 1. Subsequently, Tulsi, Grover and Patel [TGP05] showed, using a different algorithm, that such a reduction can be achieved for all t. This method can be placed in a more general framework, where given any algorithm that produces a target state for some database f with probability of error ε, one can obtain another that makes t queries to f, and errs with probability ε2t + 1. For this method to work, we do not require prior knowledge of ε. Note that no classical randomized algorithm can reduce the error probability to significantly below εt + 1, even if ε is known. In this paper, we obtain lower bounds that show that the amplification achieved by these quantum algorithms is essentially optimal. We also present simple alternative algorithms that achieve the same bound as those in Grover [G05], and have some other desirable properties. We then study the best reduction in error that can be achieved by a t-query quantum algorithm, when the initial error ε is known to lie in an interval of the form [ℓ, u]. We generalize our basic algorithms and lower bounds, and obtain nearly tight bounds in this setting.
AbstractList We consider the quantum database search problem, where we are given a function f: [N] → 0,1, and are required to return an x ∈ [N] (a target address) such that f(x)=1. Recently, Grover [G05] showed that there is an algorithm that after making one quantum query to the database, returns an X ∈ [N] (a random variable) such that $$ \Pr[f(X)=0] = \epsilon^3,$$ where ε = |f− − 1(0)|/N. Using the same idea, Grover derived a t-query quantum algorithm (for infinitely many t) that errs with probability only ε2 t + 1. Subsequently, Tulsi, Grover and Patel [TGP05] showed, using a different algorithm, that such a reduction can be achieved for all t. This method can be placed in a more general framework, where given any algorithm that produces a target state for some database f with probability of error ε, one can obtain another that makes t queries to f, and errs with probability ε2t + 1. For this method to work, we do not require prior knowledge of ε. Note that no classical randomized algorithm can reduce the error probability to significantly below εt + 1, even if ε is known. In this paper, we obtain lower bounds that show that the amplification achieved by these quantum algorithms is essentially optimal. We also present simple alternative algorithms that achieve the same bound as those in Grover [G05], and have some other desirable properties. We then study the best reduction in error that can be achieved by a t-query quantum algorithm, when the initial error ε is known to lie in an interval of the form [ℓ, u]. We generalize our basic algorithms and lower bounds, and obtain nearly tight bounds in this setting.
Author Raghunathan, Nandakumar
Chakraborty, Sourav
Radhakrishnan, Jaikumar
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Notes Original Abstract: We consider the quantum database search problem, where we are given a function f: [N] → {0,1}, and are required to return an x ∈ [N] (a target address) such that f(x)=1. Recently, Grover [G05] showed that there is an algorithm that after making one quantum query to the database, returns an X ∈ [N] (a random variable) such that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \Pr[f(X)=0] = \epsilon^3,$$\end{document} where ε = |f− − 1(0)|/N. Using the same idea, Grover derived a t-query quantum algorithm (for infinitely many t) that errs with probability only ε2 t + 1. Subsequently, Tulsi, Grover and Patel [TGP05] showed, using a different algorithm, that such a reduction can be achieved for all t. This method can be placed in a more general framework, where given any algorithm that produces a target state for some database f with probability of error ε, one can obtain another that makes t queries to f, and errs with probability ε2t + 1. For this method to work, we do not require prior knowledge of ε. Note that no classical randomized algorithm can reduce the error probability to significantly below εt + 1, even if ε is known. In this paper, we obtain lower bounds that show that the amplification achieved by these quantum algorithms is essentially optimal. We also present simple alternative algorithms that achieve the same bound as those in Grover [G05], and have some other desirable properties. We then study the best reduction in error that can be achieved by a t-query quantum algorithm, when the initial error ε is known to lie in an interval of the form [ℓ, u]. We generalize our basic algorithms and lower bounds, and obtain nearly tight bounds in this setting.
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PublicationSubtitle 8th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005 and 9th International Workshop on Randomization and Computation, RANDOM 2005, Berkeley, CA, USA, August 22-24, 2005. Proceedings
PublicationTitle Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques
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Snippet We consider the quantum database search problem, where we are given a function f: [N] → 0,1, and are required to return an x ∈ [N] (a target address) such that...
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springer
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StartPage 245
SubjectTerms Algorithmics. Computability. Computer arithmetics
Applied sciences
Computer science; control theory; systems
Error Reduction
Exact sciences and technology
Quantum Algorithm
Quantum Circuit
Quantum Search
Target Address
Theoretical computing
Title Bounds for Error Reduction with Few Quantum Queries
URI http://link.springer.com/10.1007/11538462_21
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