Quantum Algorithm Cards : Streamlining the Development of Hybrid Classical-Quantum Applications
Stirbu, V., & Haghparast, M. (2023). Quantum Algorithm Cards : Streamlining the Development of Hybrid Classical-Quantum Applications. In R. Kadgien, A. Jedlitschka, A. Janes, V. Lenarduzzi, & X. Li (Eds.), Product-Focused Software Process Improvement : 24th International Conference, PROFES 2023, Dornbirn, Austria, December 10–13, 2023, Proceedings, Part I (14483, pp. 125-130). Springer. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-031-49269-3_13
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Lecture Notes in Computer ScienceEditors
Date
2023Copyright
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
The emergence of quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. The ability of quantum computers to scale computations implies better performance and efficiency for certain algorithmic tasks than current computers provide. However, to gain benefit from such improvement, quantum computers must be integrated with existing software systems, a process that is not straightforward. In this paper, we investigate challenges that emerge when building larger hybrid classical-quantum computers and introduce the Quantum Algorithm Card (QAC) concept, an approach that could be employed to facilitate the decision making process around quantum technology.
Publisher
SpringerParent publication ISBN
978-3-031-49268-6Conference
International Conference on Product-Focused Software Process ImprovementIs part of publication
Product-Focused Software Process Improvement : 24th International Conference, PROFES 2023, Dornbirn, Austria, December 10–13, 2023, Proceedings, Part IISSN Search the Publication Forum
0302-9743Keywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/194745902
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Research Council of Finland; Business FinlandFunding program(s)
Academy Project, AoF; Co-Innovation, BFAdditional information about funding
This work has been supported by the Academy of Finland (project DEQSE 349945) and Business Finland (project TORQS 8582/31/2022).License
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