The Holy Grail of Quantum Artificial Intelligence: Major Challenges in Accelerating the Machine Learning Pipeline

Gabor, Thomas; Leo, Sünkel,; Ritz, Fabian; Phan, Thomy; Belzner, Lenz; Roch, Christoph; Feld, Sebastian; Linnhoff‐Popien, Claudia

doi:10.48550/arxiv.2004.14035

Cited by 1 publication

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“…Quantum computing promises to solve many problems more efficiently or precisely than possible with classical computers, e.g., simulating complex physical systems or applying machine learning techniques [5,6,25]. With recent advances in developing more powerful quantum computers, also the development of corresponding quantum software and applications, as well as their integration into existing software architectures, are becoming increasingly important [49,66].…”

Section: Introductionmentioning

confidence: 99%

The Quantum software lifecycle

Weder

Barzen

Leymann

et al. 2020

Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software

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With recent advances in the development of more powerful quantum computers, the research area of quantum software engineering is emerging, having the goal to provide concepts, principles, and guidelines to develop high-quality quantum applications. In classical software engineering, lifecycles are used to document the process of designing, implementing, maintaining, analyzing, and adapting software. Such lifecycles provide a common understanding of how to develop and operate an application, which is especially important due to the interdisciplinary nature of quantum computing. Since today's quantum applications are, in most cases, hybrid, consisting of quantum and classical programs, the lifecycle for quantum applications must involve the development of both kinds of programs. However, the existing lifecycles only target the development of quantum or classical programs in isolation. Additionally, the various programs must be orchestrated, e.g., using workflows. Thus, the development of quantum applications also incorporates the workflow lifecycle. In this chapter, we analyze the software artifacts usually comprising a quantum application and present their corresponding lifecycles. Furthermore, we identify the points of connection between the various lifecycles and integrate them into the overall quantum software development lifecycle. Therefore, the integrated lifecycle serves as a basis for the development and execution of hybrid quantum applications.

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