C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
Quantum Software Engineering (QSE) is emerging as a critical discipline to make quantum computing accessible to a broader developer community; however, most quantum development environments still require developers to engage with low-level details across the software stack—including problem encoding, circuit construction, algorithm configuration, hardware selection, and result interpretation—making them difficult for classical software engineers to use. To bridge this gap, we present C2 \(\lvert Q \rangle\) , a hardware-agnostic quantum software development framework that translates specific types of classical specifications into quantum-executable programs while preserving methodological rigor. The framework applies modular software engineering principles by classifying the workflow into three core modules: an encoder that classifies problems, produces Quantum-Compatible Formats (QCFs), and constructs quantum circuits, a deployment module that generates circuits and recommends hardware based on fidelity, runtime, and cost, and a decoder that interprets quantum outputs into classical solutions. This architecture supports systematic evaluation across simulators and Noisy Intermediate-Scale Quantum (NISQ) quantum devices, remaining scalable to new problem classes and algorithms. In evaluation, the encoder module achieved a 93.8% completion rate, the hardware recommendation module consistently selected the appropriate quantum devices for workloads scaling up to 56 qubits. End-to-end experiments on 434 Python programs and 100 JSON problem instances demonstrate that the full C2 \(\lvert Q \rangle\) workflow executes reliably on simulators and can be deployed successfully on representative real quantum hardware, with empirical runs limited to small- and medium-sized instances consistent with current NISQ capabilities. A proxy-based usability analysis further indicates substantial reductions in handwritten lines of code and explicit configuration steps compared to conventional quantum SDK workflows. These results indicate that C2 \(\lvert Q \rangle\) lowers the entry barrier to quantum software development by providing a reproducible, extensible toolchain that connects classical specifications to quantum execution. The open-source implementation of C2 \(\lvert Q \rangle\) is available at https://github.com/C2-Q/C2Q and as a ready-to-use Python package at https://pypi.org/project/c2q-framework/.