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On Decision Support for Quantum Application Developers: Categorization, Comparison, and Analysis of Existing Technologies

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Computational Science – ICCS 2021 (ICCS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12747))

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Abstract

Quantum computers have been significantly advanced in recent years. Offered as cloud services, quantum computers have become accessible to a broad range of users. Along with the physical advances, the landscape of technologies supporting quantum application development has also grown rapidly in recent years. However, there is a variety of tools, services, and techniques available for the development of quantum applications, and which ones are best suited for a particular use case depends, among other things, on the quantum algorithm and quantum hardware. Thus, their selection is a manual and cumbersome process. To tackle this challenge, we introduce a categorization and a taxonomy of available tools, services, and techniques for quantum application development to enable their analysis and comparison. Based on that we further present a comparison framework to support quantum application developers in their decision for certain technologies.

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Notes

  1. 1.

    https://qosf.org.

  2. 2.

    The framework can be found at http://www.github.com/UST-QuAntiL/Qverview.

  3. 3.

    QPUs are grouped by their respective vendor.

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Acknowledgments

This work was partially funded by the BMWi project PlanQK (01MK20005N) as well as the WM BW project SEQUOIA.

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Authors and Affiliations

  1. Institute of Architecture of Application Systems, University of Stuttgart, Universitätsstraße 38, 70569, Stuttgart, Germany

    Daniel Vietz, Johanna Barzen, Frank Leymann & Karoline Wild

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  1. Daniel Vietz
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  4. Karoline Wild
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Corresponding author

Correspondence to Daniel Vietz .

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Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Dieter Kranzlmüller

  3. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  4. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  5. University of Amsterdam, Amsterdam, The Netherlands

    Peter M. A. Sloot

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Vietz, D., Barzen, J., Leymann, F., Wild, K. (2021). On Decision Support for Quantum Application Developers: Categorization, Comparison, and Analysis of Existing Technologies. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12747. Springer, Cham. https://doi.org/10.1007/978-3-030-77980-1_10

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