Quantum computing is rapidly evolving into an emerging computational infrastructure and is increasingly being used to tackle real-world problems in domains such as chemistry, materials science, logistics, and finance, as well as software engineering problems such as test optimization and project scheduling. Hybrid quantum-classical applications are particularly important because they provide a practical path for integrating quantum capabilities into existing software systems under near-term hardware constraints. However, the engineering of hybrid quantum-classical applications remains largely ad hoc and constrained by hardware limitations including qubit scarcity, noise, and limited connectivity. In this paper, we propose Q-READY to address the lack of systematic methodologies for assessing the feasibility of hybrid solutions prior to costly implementation. Positioned as a Model-Based Systems Engineering (MBSE) approach grounded in Model-Driven Engineering (MDE) principles, Q-READY establishes a structured pipeline encompassing requirements modeling, problem formulation, workflow design, and hardware-aware feasibility assessment, enabling simulation-based evaluation and comparison of candidate solutions under realistic constraints through traceable system-level models and backend-aware abstractions. We illustrate the pipeline with a running credit-portfolio capital-assessment example, showing how requirements, problem structure, strategy choices, workflow behavior, backend assumptions, and feasibility evidence can be linked into a coherent engineering decision. Q-READY is envisioned as an environment that supports executable modeling, constraint evaluation, and predictive analysis. Its expected outcomes include a systematic methodology for hybrid quantum application design, a supporting software platform, benchmark datasets, and empirical design guidelines.

翻译：量子计算正快速演进为新兴的计算基础设施，并日益被用于解决化学、材料科学、物流和金融等领域的现实问题，以及测试优化和项目调度等软件工程问题。混合量子-经典应用尤为重要，因为它们提供了一条在近期硬件约束下将量子能力集成到现有软件系统中的实用路径。然而，混合量子-经典应用的工程实践在很大程度上仍依赖临时方案，并受到量子比特稀缺、噪声和有限连通性等硬件限制。在本文中，我们提出Q-READY，以解决在代价高昂的实施之前缺乏系统方法来评估混合解决方案可行性的问题。作为基于模型驱动工程（MDE）原则并定位为基于模型的系统工程（MBSE）的方法，Q-READY建立了一个结构化流程，涵盖需求建模、问题定义、工作流设计和硬件感知可行性评估。通过可追溯的系统级模型和后端感知抽象，它能够在现实约束下对候选解决方案进行基于仿真的评估和比较。我们以信用组合资本评估的运行示例说明该流程，展示如何将需求、问题结构、策略选择、工作流行为、后端假设和可行性证据关联为一个连贯的工程决策。Q-READY被设想为一个支持可执行建模、约束评估和预测分析的环境。其预期成果包括混合量子应用设计的系统方法、配套软件平台、基准数据集以及经验性设计指南。