Analysis of grover's quantum search algorithm on a classical computer: Identifying opportunities for improvement

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Özet

In this paper, Grover’s quantum search algorithm is analyzed using a classical computer by calculating the amplitudes and the probabilities of finding a single marked state for n=5, 10, 15, 20, 25, and 27 qubit states. The calculations show that the marked state can be found in iterations, where N = 2n is the number of items. The possibility of improving Grover’s search algorithm to find a single item in N search elements is discussed by calculating the amplitudes and hence the probabilities of finding a single marked state for n=5, 10, 15, 20, 25, 30, 35, 40, 45, and 50 qubit states. The calculations showed that the marked state could be found with sufficiently high probability in (ln(N)) iterations. This is quite a remarkable speed-up that can be achieved to find a single marked element in an unsorted N search element. Copyright 2021, Yıldız Technical University.

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https://rdlopen.rawdatalibrary.net/r/gumushane/12439Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.14744/sigma.2023.00069Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorNecati, Çeli̇K
dc.contributor.authorBi̇Ngöl, Özkan
dc.date.accessioned2026-10-22T10:20:07.116633851Z
dc.date.available2026-10-22T10:20:07.116633851Z
dc.date.issued2024
dc.description.abstractIn this paper, Grover’s quantum search algorithm is analyzed using a classical computer by calculating the amplitudes and the probabilities of finding a single marked state for n=5, 10, 15, 20, 25, and 27 qubit states. The calculations show that the marked state can be found in iterations, where N = 2n is the number of items. The possibility of improving Grover’s search algorithm to find a single item in N search elements is discussed by calculating the amplitudes and hence the probabilities of finding a single marked state for n=5, 10, 15, 20, 25, 30, 35, 40, 45, and 50 qubit states. The calculations showed that the marked state could be found with sufficiently high probability in (ln(N)) iterations. This is quite a remarkable speed-up that can be achieved to find a single marked element in an unsorted N search element. Copyright 2021, Yıldız Technical University.
dc.identifier.doi10.14744/sigma.2023.00069
dc.identifier.eissn1304-7191
dc.identifier.endpage1049
dc.identifier.issn1304-7191
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85200756200
dc.identifier.startpage1039
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/12439
dc.identifier.volume42
dc.identifier.wosWOS:001316114100009
dc.language.isoen
dc.publisherYildiz Technical University
dc.relation.ispartofSigma Journal of Engineering and Natural Sciences
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectGrover’s Search Algorithm
dc.subjectQuantum Information
dc.subjectQuantum Information Processing
dc.subjectQubit, State Vector
dc.subject.classificationEngineering, Multidisciplinary
dc.subject.classificationEngineering
dc.subject.otherIMPLEMENTATION
dc.subject.otherSTABILIZATION
dc.subject.otherREALIZATION
dc.titleAnalysis of grover's quantum search algorithm on a classical computer: Identifying opportunities for improvement
dc.typeArticle
dspace.entity.typePublication
rdl.citation.openalex5
rdl.citation.scopus2
rdl.citation.wos1
rdl.oa.statusgold
rdl.oa.urlhttps://doi.org/10.14744/sigma.2023.00069
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexEmerging Sources Citation Index (ESCI)