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arxiv: 2604.04112 · v1 · submitted 2026-04-05 · 💻 cs.SE

C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development -- RCR Report

Boshuai Ye , Arif Ali Khan , Teemu Pihkakoski , Peng Liang , Muhammad Azeem Akbar , Matti Silveri , Lauri Malmi This is my paper

Pith reviewed 2026-05-13 17:18 UTC · model grok-4.3

classification 💻 cs.SE
keywords quantum software frameworkclassical to quantum translationproblem familieshardware agnosticreplication reportpretrained parser modelPyPI package
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The pith

The C2|Q> framework converts classical Python code or JSON specifications into executable quantum programs for ten problem families across multiple hardware backends.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The report presents a modular translator that accepts ordinary Python or structured JSON descriptions of classical problems and produces ready-to-run quantum programs. It covers ten distinct problem families and works with several quantum hardware platforms without requiring users to write device-specific code. The authors supply a pretrained parser model, full source code, evaluation data sets, and a PyPI package so that the three main experiments can be re-run directly from documented commands. Successful replication confirms that the translation pipeline functions as described and can be used by developers who start from classical specifications.

Core claim

A single modular, hardware-agnostic pipeline accepts either Python source or JSON problem descriptions, parses them with a pretrained model, and emits executable quantum programs that run on multiple backends; the replication report verifies that the released model, code repository, and data files allow exact reproduction of the original translation results for Experiments 1 through 3.

What carries the argument

The modular translator that maps classical Python or JSON problem specifications to quantum programs using a pretrained parser model.

If this is right

  • Developers can describe a classical problem once and obtain working quantum code without learning hardware-specific syntax.
  • The same pipeline supports ten problem families and multiple quantum backends from a single set of inputs.
  • Reproduction of the reported results is possible using only the public pretrained model and the provided make commands.
  • Lightweight CLI and API access is available through the released PyPI package.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The approach could let classical programmers prototype quantum versions of their existing code with minimal extra effort.
  • Extending the parser to additional problem families would increase the framework's coverage without changing its input format.
  • Integration of the PyPI package into standard Python workflows would allow automated quantum translation inside larger classical applications.

Load-bearing premise

The released pretrained model, GitHub repository, Zenodo data, and make targets contain everything needed to reproduce the original experiments without hidden dependencies or extra manual steps.

What would settle it

Running the documented make targets from the GitHub repository on a fresh environment and checking whether Experiments 2 and 3 complete and produce the expected outputs without errors or missing artifacts.

read the original abstract

This is the Replicated Computational Results (RCR) Report for the paper C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development. The paper introduces a modular, hardware-agnostic framework that translates classical problem specifications - Python code or structured JSON - into executable quantum programs across ten problem families and multiple hardware backends. We release the framework source code on GitHub at https://github.com/C2-Q/C2Q, a pretrained parser model on Zenodo at https://zenodo.org/records/19061125, evaluation data in a separate Zenodo record at https://zenodo.org/records/17071667, and a PyPI package at https://pypi.org/project/c2q-framework/ for lightweight CLI and API use. Experiment 1 is supported through a released pretrained model and training notebook, while Experiments 2 and 3 are directly executable via documented make targets. This report describes the artifact structure, setup instructions, and the mapping from each execution route to the corresponding experiment.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 2 minor

Summary. The manuscript is the Replicated Computational Results (RCR) Report accompanying the paper 'C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development'. It claims that the C2|Q> framework provides a modular, hardware-agnostic translation from classical problem specifications (Python code or structured JSON) to executable quantum programs across ten problem families and multiple hardware backends. The report details the public release of the source code on GitHub, a pretrained parser model on Zenodo, evaluation data on a separate Zenodo record, a PyPI package for CLI/API access, a training notebook, and documented make targets that map directly to replication of Experiments 1-3.

Significance. If the artifacts function as described, the work provides a valuable contribution to quantum software engineering by lowering barriers to replication in a field where hardware access and configuration complexity often impede verification. Explicit credit is due for the release of the pretrained model, full source code, evaluation data, PyPI package, and make targets that enable direct execution of the claimed experiments; these elements constitute a concrete, community-accessible reproducibility package rather than abstract claims.

minor comments (2)
  1. [Artifact structure and setup instructions] The mapping from make targets to Experiments 2 and 3 is described at a high level; adding a short table or explicit command list in the setup section would make the replication path fully self-contained without requiring inspection of the GitHub repository.
  2. [Abstract] The abstract states support for 'ten problem families' but does not enumerate them or cite the corresponding section of the original paper; a one-sentence list or pointer would improve accessibility for readers new to the framework.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive assessment of the RCR report and the recommendation for minor revision. We appreciate the recognition that the released artifacts—including the GitHub source code, pretrained model on Zenodo, evaluation data, PyPI package, and documented make targets—provide a concrete reproducibility package for the C2|Q> framework.

Circularity Check

0 steps flagged

No significant circularity: RCR report relies on external artifact releases with no derivations or self-referential reductions

full rationale

This RCR report contains no equations, predictions, or derivation chains. Its central claim is supported by public releases of code, pretrained models, data, and packages on GitHub, Zenodo, and PyPI, with explicit make targets mapping to Experiments 1-3. No steps reduce by construction to fitted parameters or self-citations; the structure is self-contained via external benchmarks (reproducible artifacts) rather than internal definitions. This matches the default expectation of no circularity for artifact-focused reports.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

No mathematical derivations, free parameters, axioms, or invented physical entities are present. The contribution consists entirely of released software artifacts and replication instructions.

pith-pipeline@v0.9.0 · 5508 in / 1164 out tokens · 50023 ms · 2026-05-13T17:18:56.515711+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

5 extracted references · 5 canonical work pages

  1. [1]

    c2q-framework

    2025. c2q-framework. https://pypi.org/project/c2q-framework/. Accessed: 2026-03-18

    work page 2025

  2. [2]

    Boshuai Ye and Arif Ali Khan. 2025. C2|Q> Evaluation Dataset and Artifact Archive. https://zenodo.org/records/17071667. Accessed: 2026-03-18

    work page arXiv 2025

  3. [3]

    Boshuai Ye and Arif Ali Khan. 2025. C2|Q> Parser Model Archive. https://zenodo.org/records/19061126. Accessed: 2026-03-18. Manuscript submitted to ACM 12 Ye et al

    work page arXiv 2025

  4. [4]

    Boshuai Ye, Arif Ali Khan, Teemu Pihkakoski, Peng Liang, Muhammad Azeem Akbar, Matti Silveri, and Lauri Malmi. 2025. C2|Q> GitHub Repository. https://github.com/C2-Q/C2Q. Accessed: 2026-03-18

    work page 2025

  5. [5]

    Boshuai Ye, Arif Ali Khan, Teemu Pihkakoski, Peng Liang, Muhammad Azeem Akbar, Matti Silveri, and Lauri Malmi. 2026. C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development.ACM Trans. Softw. Eng. Methodol.(March 2026). https://doi.org/10.1145/3803018 Just Accepted. Manuscript submitted to ACM

    work page doi:10.1145/3803018 2026