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Hybrid Data Management Architecture for Present Quantum Computing

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Service-Oriented Computing – ICSOC 2023 Workshops (ICSOC 2023)

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Abstract

Quantum computers promise polynomial or exponential speed-up in solving certain problems compared to classical computers. However, in practical use, there are currently a number of fundamental technical challenges. One of them concerns the loading of data into quantum computers, since they cannot access common databases. In this vision paper, we develop a hybrid data management architecture in which databases can serve as data sources for quantum algorithms. To test the architecture, we perform experiments in which we assign data points stored in a database to clusters. For cluster assignment, a quantum algorithm processes this data by determining the distances between data points and cluster centroids.

This work has been funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) grant #385808805. We would like to thank Stefanie Scherzinger from University of Passau for many prolific discussions as well as helpful suggestions.

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Notes

  1. 1.

    IBM Quantum. https://quantum.ibm.com/, 2023.

References

  1. Çalikyilmaz, U., et al.: Opportunities for quantum acceleration of databases: optimization of queries and transaction schedules. Proc. VLDB Endow. 16(9), 2344–2353 (2023)

    Article  Google Scholar 

  2. David, C.: Complexity of data tree patterns over XML documents. In: Ochmański, E., Tyszkiewicz, J. (eds.) MFCS 2008. LNCS, vol. 5162, pp. 278–289. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85238-4_22

    Chapter  Google Scholar 

  3. DiAdamo, S., O’Meara, C., Cortiana, G., Bernabé-Moreno, J.: Practical quantum K-means clustering: performance analysis and applications in energy grid classification. IEEE Trans. Quant. Eng. 3, 1–16 (2022)

    Article  Google Scholar 

  4. Dragoni, N., et al.: Microservices: yesterday, today, and tomorrow. In: Mazzara, M., Meyer, B. (eds.) Present and Ulterior Software Engineering, pp. 195–216. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67425-4_12

    Chapter  Google Scholar 

  5. Gottlob, G., Koch, C., Pichler, R.: The complexity of XPath query evaluation. In: Proceedings of the PODS 2003, pp. 179–190. ACM (2003)

    Google Scholar 

  6. Hassija, V., Chamola, V., Goyal, A., Kanhere, S.S., Guizani, N.: Forthcoming applications of quantum computing: peeking into the future. IET Quant. Commun. 1(2), 35–41 (2020)

    Article  Google Scholar 

  7. Herbert, S.: Quantum computing for data-centric engineering and science. Data-Cent. Eng. 3, e36 (2022)

    Article  Google Scholar 

  8. Houssein, E.H., Abohashima, Z., Elhoseny, M., Mohamed, W.M.: Machine learning in the quantum realm: the state-of-the-art, challenges, and future vision. Expert Syst. Appl. 194, 116512 (2022)

    Article  Google Scholar 

  9. Jóczik, S., Kiss, A.: Quantum computation and its effects in database systems. In: Darmont, J., Novikov, B., Wrembel, R. (eds.) ADBIS 2020. CCIS, vol. 1259, pp. 13–23. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-54623-6_2

    Chapter  Google Scholar 

  10. Kieferová, M., Sanders, Y.: Assume a quantum data set. Harv. Data Sci. Rev. 4(1) (2022)

    Google Scholar 

  11. Kraska, T., et al.: Check out the big brain on BRAD: simplifying cloud data processing with learned automated data meshes. Proc. VLDB Endow. 16(11), 3293–3301 (2023)

    Article  Google Scholar 

  12. Leymann, F., Barzen, J.: The bitter truth about gate-based quantum algorithms in the NISQ era. Quant. Sci. Technol. 5(4), 044007 (2020)

    Article  Google Scholar 

  13. Liu, J., Hann, C.T., Jiang, L.: Data centers with quantum random access memory and quantum networks. Phys. Rev. A 108, 032610 (2023)

    Article  Google Scholar 

  14. Manolescu, I., Mohanty, M.: Full-power graph querying: state of the art and challenges. Proc. VLDB Endow. 16(12), 3886–3889 (2023)

    Article  Google Scholar 

  15. Matteo, O.D., Gheorghiu, V., Mosca, M.: Fault-tolerant resource estimation of quantum random-access memories. IEEE Trans. Quant. Eng. 1, 1–13 (2020)

    Article  Google Scholar 

  16. Ouedrhiri, O., Banouar, O., Raghay, S., el Hadaj, S.: Comparative study of data preparation methods in quantum clustering algorithms. In: NISS (ACM), pp. 28:1–28:5. ACM (2021)

    Google Scholar 

  17. Phalak, K., Chatterjee, A., Ghosh, S.: Quantum random access memory for dummies. CoRR abs/2305.01178 (2023)

    Google Scholar 

  18. Qiskit contributors: Qiskit: An Open-source Framework for Quantum Computing (2023). https://doi.org/10.5281/zenodo.2573505

  19. Riel, H.: Quantum computing technology. In: 2021 IEEE International Electron Devices Meeting (IEDM) (2021)

    Google Scholar 

  20. Schuld, M., Petruccione, F.: Quantum computing. In: Schuld, M., Petruccione, F. (eds.) Machine Learning with Quantum Computers. Quantum Science and Technology, pp. 79–146. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-83098-4_3

    Chapter  Google Scholar 

  21. Schuld, M., Petruccione, F.: Representing data on a quantum computer. In: Schuld, M., Petruccione, F. (eds.) Machine Learning with Quantum Computers. QST, pp. 147–176. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-83098-4_4

    Chapter  Google Scholar 

  22. Weder, B., Barzen, J., Leymann, F., Zimmermann, M.: Hybrid quantum applications need two orchestrations in superposition: a software architecture perspective. In: 2021 IEEE International Conference on Web Services (ICWS), pp. 1–13 (2021)

    Google Scholar 

  23. Weigold, M., Barzen, J., Leymann, F., Salm, M.: Encoding patterns for quantum algorithms. IET Quant. Commun. 2(4), 141–152 (2021)

    Article  Google Scholar 

  24. Weigold, M., Barzen, J., Leymann, F., Salm, M.: Expanding data encoding patterns for quantum algorithms. In: 2021 IEEE 18th International Conference on Software Architecture Companion (ICSA-C), pp. 95–101. IEEE (2021–03)

    Google Scholar 

  25. Weigold, M., Barzen, J., Leymann, F., Salm, M.: Data encoding patterns for quantum computing. In: Proceedings of the 27th Conference on Pattern Languages of Programs, PLoP 2020. The Hillside Group (2022)

    Google Scholar 

  26. Weigold, M., Barzen, J., Leymann, F., Vietz, D.: Patterns for hybrid quantum algorithms. In: Barzen, J. (ed.) SummerSOC 2021. CCIS, vol. 1429, pp. 34–51. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-87568-8_2

    Chapter  Google Scholar 

  27. Yuan, G., et al.: Quantum computing for databases: a short survey and vision. In: VLDB Workshops. CEUR Workshop Proceedings, vol. 3462. CEUR-WS.org (2023)

    Google Scholar 

  28. Zajac, M.: Encoding and provisioning data in different data models for quantum computing. In: PhD@VLDB. CEUR Workshop Proceedings, vol. 3452, pp. 45–48. CEUR-WS.org (2023)

    Google Scholar 

  29. Zajac, M., Störl, U.: Towards quantum-based search for industrial data-driven services. In: Proceedings of the 2022 IEEE International Conference on Quantum Software (QSW). IEEE (2022)

    Google Scholar 

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Authors and Affiliations

  1. Databases and Information Systems, FernUniversität in Hagen, Hagen, Germany

    Markus Zajac & Uta Störl

Authors
  1. Markus Zajac
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  2. Uta Störl
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Corresponding author

Correspondence to Markus Zajac .

Editor information

Editors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Flavia Monti

  2. Politecnico di Milano, Milan, Italy

    Pierluigi Plebani

  3. École de Technologie Supérieure, Montréal, QC, Canada

    Naouel Moha

  4. University of New South Wales, Sydney, NSW, Australia

    Hye-young Paik

  5. University of Stuttgart, Stuttgart, Germany

    Johanna Barzen

  6. Queensland University of Technology, Brisbane, QLD, Australia

    Gowri Ramachandran

  7. University of Brescia, Brescia, Italy

    Devis Bianchini

  8. TU/e – JADS, Politecnico di Milano, Milan, Italy

    Damian A. Tamburri

  9. Sapienza University of Rome, Rome, Italy

    Massimo Mecella

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Zajac, M., Störl, U. (2024). Hybrid Data Management Architecture for Present Quantum Computing. In: Monti, F., et al. Service-Oriented Computing – ICSOC 2023 Workshops. ICSOC 2023. Lecture Notes in Computer Science, vol 14518. Springer, Singapore. https://doi.org/10.1007/978-981-97-0989-2_14

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  • DOI: https://doi.org/10.1007/978-981-97-0989-2_14

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  • Print ISBN: 978-981-97-0988-5

  • Online ISBN: 978-981-97-0989-2

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