Q-READY: Predictive Feasibility Assessment for Hybrid Quantum-Classical Applications
2026-06-15 • Software Engineering
Software EngineeringComputational Engineering, Finance, and Science
AI summaryⓘ
The authors present Q-READY, a new method to help engineers figure out if hybrid quantum-classical computing solutions will work before spending time building them. This method uses structured models to connect the problem requirements, possible solutions, and hardware limits like noise and few qubits. It allows users to simulate and compare different approaches while considering real hardware constraints. The authors demonstrate Q-READY with a financial example to show how it helps make better engineering decisions for combining quantum and classical computing. Their goal is to create a clear, repeatable process and tools for designing hybrid quantum applications.
Quantum computingHybrid quantum-classical applicationsModel-Based Systems Engineering (MBSE)Model-Driven Engineering (MDE)QubitsNoise in quantum systemsFeasibility assessmentSimulationWorkflow designHardware-aware abstraction
Authors
Tao Yue, Man Zhang
Abstract
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.