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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-29643
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dc.contributor.authorFankhauser, Tobias-
dc.contributor.authorSolèr, Marc E.-
dc.contributor.authorFüchslin, Rudolf Marcel-
dc.contributor.authorStockinger, Kurt-
dc.date.accessioned2024-01-19T10:37:40Z-
dc.date.available2024-01-19T10:37:40Z-
dc.date.issued2023-10-
dc.identifier.issn2169-3536de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/29643-
dc.description.abstractQuantum computing promises to solve difficult optimization problems in chemistry, physics and mathematics more efficiently than classical computers. However, it requires fault-tolerant quantum computers with millions of qubits; a technological challenge still not mastered by engineers. To lower the barrier, hybrid algorithms combining classical and quantum computers are used, where quantum computing is only used for those parts of computation that cannot be solved efficiently otherwise. In this paper, we tackle the multiple query optimization problem (MQO), an important NP-hard problem in database research. We present an implementation based on a scheme called quantum approximate optimization algorithm to solve the MQO on a gate-based quantum computer. We perform a detailed experimental evaluation of our implementation and compare its performance against a competing approach that employs a quantum annealer – another type of quantum computer. Our implementation shows a qubit efficiency of close to 99%, which is almost a factor of 2 higher than the state-of-the-art implementation. We emphasize that the problems we can solve with current gate-based quantum technology are fairly small and might not seem practical yet compared to state-of-the-art classical query optimizers. However, our experiments on using a hybrid approach of classical and quantum computing show that our implementation scales favourably with larger problem sizes. Hence, we conclude that our approach shows promising results for near-term quantum computers and thus sets the stage for a challenging avenue of novel database research.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.relation.ispartofIEEE Accessde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectOptimizationde_CH
dc.subjectDatabasede_CH
dc.subjectMultiple query optimizationde_CH
dc.subjectQuantum approximate optimization algorithmde_CH
dc.subjectExperimental evaluationde_CH
dc.subjectQuantum computingde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleMultiple query optimization using a gate-based quantum computerde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
zhaw.organisationalunitInstitut für Angewandte Mathematik und Physik (IAMP)de_CH
dc.identifier.doi10.1109/ACCESS.2023.3324253de_CH
dc.identifier.doi10.21256/zhaw-29643-
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end114043de_CH
zhaw.pages.start114031de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume11de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedIntelligent Information Systemsde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Fankhauser, T., Solèr, M. E., Füchslin, R. M., & Stockinger, K. (2023). Multiple query optimization using a gate-based quantum computer. IEEE Access, 11, 114031–114043. https://doi.org/10.1109/ACCESS.2023.3324253
Fankhauser, T. et al. (2023) ‘Multiple query optimization using a gate-based quantum computer’, IEEE Access, 11, pp. 114031–114043. Available at: https://doi.org/10.1109/ACCESS.2023.3324253.
T. Fankhauser, M. E. Solèr, R. M. Füchslin, and K. Stockinger, “Multiple query optimization using a gate-based quantum computer,” IEEE Access, vol. 11, pp. 114031–114043, Oct. 2023, doi: 10.1109/ACCESS.2023.3324253.
FANKHAUSER, Tobias, Marc E. SOLÈR, Rudolf Marcel FÜCHSLIN und Kurt STOCKINGER, 2023. Multiple query optimization using a gate-based quantum computer. IEEE Access. Oktober 2023. Bd. 11, S. 114031–114043. DOI 10.1109/ACCESS.2023.3324253
Fankhauser, Tobias, Marc E. Solèr, Rudolf Marcel Füchslin, and Kurt Stockinger. 2023. “Multiple Query Optimization Using a Gate-Based Quantum Computer.” IEEE Access 11 (October): 114031–43. https://doi.org/10.1109/ACCESS.2023.3324253.
Fankhauser, Tobias, et al. “Multiple Query Optimization Using a Gate-Based Quantum Computer.” IEEE Access, vol. 11, Oct. 2023, pp. 114031–43, https://doi.org/10.1109/ACCESS.2023.3324253.


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