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

arXiv: https://arxiv.org/abs/2606.16201 · HTML: https://mlsanity.com/paper/2606.16201/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jun 2026.

## Built on by (most cited first, 1 of 1)

- [Leveraging LLM-Based Agentic Systems to Generate Quantum Applications for Test Optimization](https://mlsanity.com/paper/2607.00939/) (2026)

## Abstract (arXiv)

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.