Quantum Programming

Beihang Team Structures Quantum Computing for Better Software Design

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November 2, 2026 by Ivy Delaney

Current representations of quantum software exhibit varying levels of abstraction. This inconsistency poses challenges for the Quantum Software Engineering (QSE) community. A conceptual model called QSoftCore reorganizes established Quantum Computing (QC) concepts from a software engineering perspective. QSoftCore connects quantum applications, computational problems, algorithms, configurations, programs, and paradigm-specific computation specifications with state evolution, execution Results, and backends. Assessment against QSE literature across key software engineering activities indicates that QSoftCore provides shared QC referents for quantum computations, executions, deployment configurations, backends, and measurement evidence.

QSoftCore unifies quantum software engineering views for lifecycle artifact sharing

Tao Yue, Yuechen Li and Man Zhang (Affiliation: Beihang University) developed QSoftCore, a conceptual model covering five key views within quantum software engineering. It expands existing QC concepts by explicitly representing alternative paradigms, deployment contexts, execution evidence, and raw versus mitigated results; prior methods lacked these elements. Core quantum computing ideas previously fragmented across varying abstraction levels now benefit from shared referents for computations, deployments, and measurement evidence throughout the entire lifecycle of quantum software development, allowing reuse of artifacts between studies where this was impossible before.

QSoftCore reorganises established quantum computing concepts with an eye to software engineering principles, connecting applications through algorithms to physical hardware deployment. Their assessment against existing literature revealed its ability to provide shared references for executions, backends, and measurement evidence during activities like requirements gathering, architectural design, code generation, and quality assurance.

Specifically, their model encompassed all QC concepts within reviewed papers while adding explicit representations for alternative paradigms beyond gate-based systems; it also explicitly models execution evidence, separating intended computation from actual runtime behaviour, a feature absent in prior approaches that often treat simulation results as definitive.

QSoftCore establishes foundational terminology for emerging quantum software practices

Although the QSoftCore model successfully maps onto existing approaches detailed within published literature, providing a shared vocabulary across requirements gathering through to deployment, its true value remains unproven beyond this assessment. The team acknowledges validation currently relies solely upon comparison with established work and important usability tests involving practitioners are yet to be undertaken, leaving open whether this conceptual framework genuinely streamlines workflows or simply re-packages familiar ideas. Despite lacking practical validation with working developers, it offers a valuable contribution to the nascent field of quantum software engineering.

A common language now exists for discussing complex concepts like algorithms and backends, vital as the discipline matures beyond purely theoretical exercises. This allows reuse of artifacts between research projects where inconsistent language formerly prevented collaboration; an important step as the field moves towards building practical applications. The implications are significant because establishing shared references across the entire lifecycle connects applications to deployment via algorithms and execution results.

QSoftCore establishes a conceptual model that organizes existing quantum computing concepts through a software engineering lens. This reorganization provides consistent terminology for elements like algorithms, backends, computation specifications, and measurement evidence, areas which have historically lacked unified definitions. By connecting application requirements with execution results, QSoftCore facilitates communication and artifact reuse within the quantum software engineering community. The authors note further validation is needed through usability tests involving practitioners to confirm its impact on workflows.

👉 More information
🗞 QSoftCore: A Conceptual Foundation for Quantum Software Engineering
✍️ Tao Yue, Yuechen Li and Man Zhang (Affiliation: Beihang University)
🧠 ArXiv: https://arxiv.org/abs/2610.39406

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Avatar of Ivy Delaney

Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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