Q-READY: Predictive Feasibility Assessment for Hybrid Quantum-Classical Applications

2026-06-15

AI Summary

This work addresses the lack of systematic feasibility assessment in hybrid quantum-classical application development, a gap that often leads to costly and ad hoc design processes. To overcome this challenge, the authors propose Q-READY, the first framework to integrate Model-Driven Engineering (MDE) and Model-Based Systems Engineering (MBSE) into this domain. Q-READY establishes an end-to-end feasibility prediction pipeline encompassing requirement modeling, problem formalization, workflow design, and hardware-aware simulation. The approach enables comparative analysis of alternative solutions and ensures full traceability across development stages. Supporting artifacts—including a dedicated software platform, a benchmark dataset, and design guidelines—are provided to facilitate adoption. The effectiveness of Q-READY is demonstrated through a real-world case study on credit portfolio capital assessment.

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.

Problem

• hybrid quantum-classical applications
• feasibility assessment
• quantum computing
• Model-Based Systems Engineering
• hardware constraints

Innovation

• hybrid quantum-classical computing
• Model-Based Systems Engineering (MBSE)
• hardware-aware feasibility assessment
• executable modeling
• quantum application design