Building quantum applications requires deep knowledge of quantum computing and software engineering. Hence, an abstraction layer reducing the complexity for non-experts is needed. Patterns are an established concept for the abstract description of proven solutions to recurring problems. Therefore, the quantum computing patterns, a pattern language for the quantum computing domain, can be used to define the building blocks and the structure of hybrid quantum applications. Furthermore, concrete software artifacts can be associated with patterns to solve the corresponding problem. However, these software artifacts are usually heterogeneous, e.g., using different data formats. Quantum workflows enable a robust and scalable orchestration of these heterogeneous software artifacts. However, manually modeling and configuring such quantum workflows is a complex, error-prone, and time-consuming task. To overcome this issue, we present an approach that automates the generation and adaptation of quantum workflows using the quantum computing patterns. We provide an architecture realizing our approach, a corresponding prototype, as well as an evaluation comprising different use cases, a runtime comparison, and a user study.

Quantum computers are becoming real, and they have the inherent potential to significantly impact many application domains. We sketch the basics about programming quantum computers, showing that quantum programs are typically hybrid consisting of a mixture of classical parts and quantum parts. With the advent of quantum computers in the cloud, the cloud is a fine environment for performing quantum programs. The tool chain available for creating and running such programs is sketched. As an exemplary problem we discuss efforts to implement quantum programs that are hardware independent. A use case from machine learning is outlined. Finally, a collaborative platform for solving problems with quantum computers that is currently under construction is presented.

Quantum computing introduces a new computing paradigm that promises to solve problems that cannot be solved by classical computers efficiently. Thus, quantum applications will be more and more integrated in classical applications. To bring these composite applications into production, technologies for an automated deployment and orchestration are required to avoid manual error-prone and time-consuming processes. For non-quantum applications, a variety of deployment technologies have been developed in recent years. However, the deployment of quantum applications currently differs significantly from non-quantum applications and thus, leads to a different modeling procedure for the deployment of quantum applications. To overcome these problems, we propose TOSCA4QC that introduces two deployment modeling styles based on the Topology and Orchestration Specification for Cloud Applications (TOSCA) standard for automating the deployment and orchestration of quantum applications: (i) SDK-specific modeling style to cover all technical deployment details and (ii) SDK-agnostic modeling style supporting common modeling principles. We further show how existing model-driven development (MDD) approach can be applied to refine a SDK-agnostic model to an executable SDK-specific model. We demonstrate the practical feasibility by a prototypical implementation as an extension of the TOSCA ecosystem OpenTOSCA and three case studies with IBMQ and a quantum simulator.