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 in | Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques pp. 245 - 256 |
|---|---|
| Main Authors | , , |
| Format | Book Chapter Conference Proceeding |
| Language | English |
| Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
2005
Springer |
| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9783540282396 3540282394 |
| ISSN | 0302-9743 1611-3349 |
| DOI | 10.1007/11538462_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. |
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| 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 |
| Author_xml | – sequence: 1 givenname: Sourav surname: Chakraborty fullname: Chakraborty, Sourav email: sourav@cs.uchicago.edu organization: Department of Computer Science, University of Chicago, Chicago, USA – sequence: 2 givenname: Jaikumar surname: Radhakrishnan fullname: Radhakrishnan, Jaikumar email: jaikumar@tti-c.org organization: School of Technology and Computer Science, Tata Institute of Fundamental Research, Mumbai, India – sequence: 3 givenname: Nandakumar surname: Raghunathan fullname: Raghunathan, Nandakumar email: nanda@cs.uchicago.edu organization: Department of Computer Science, University of Chicago, Chicago, USA |
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| Keywords | Error estimation Quantum computation Search algorithm |
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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 |
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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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| 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 |
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