AI 中文总结
研究量子计算研究成果的可重复性问题，通过手动评估127篇论文样本和自动筛选近5000篇论文，量化其缺陷，发现可重复性未达要求，进而给出实用建议以改进量子计算研究中的可重复性。
AI 中文摘要
量子计算研究越来越依赖复杂软件栈，但已发表成果的可重复性未得到国际大型科学机构建议及以软件为中心的系统研究最佳实践所要求的重视和长期关注。本文对量子计算研究中的可重复性情况进行了手动和自动相结合的大规模分析，量化缺陷并得出可行的推进步骤。通过一个涵盖代码可用性、环境规范、文档、硬件描述和可执行性的五问题框架手动评估了127篇论文样本，还对近5000篇量子计算论文进行了相同可重复性指标的自动大规模筛选。手动分析显示仅24.4%的抽样论文提供代码工件，其中64.5%在干净环境中无法成功执行，自动分析得出一致的代码可用性率为26.8%，约三分之一有可访问代码的论文缺乏机器可读环境规范。结果表明量子计算研究中可重复性尚未一致实现，为此概述了一系列实用建议以解决观察到的失败模式并说明如何在实践中提高可重复性。
英文摘要
Quantum computing research increasingly depends on complex software stacks, yet the reproducibility of published results does not receive the priority and longevity mandated by recommendations of large international scientific bodies and best practices in software-centric systems research. In this paper, we present a combined manual and automated large-scale analysis of the reproducibility landscape in quantum computing research, quantify shortcomings, and derive actionable steps forward. We manually evaluate a curated sample of 127 papers using a five-question framework that covers code availability, environment specification, documentation, hardware description, and executability. To place these findings in a broader context, we conduct an automated large-scale screening of nearly 5000 quantum computing papers for the same reproducibility indicators. Our manual analysis reveals that only 24.4% of the sampled papers provide code artefacts, and among those, 64.5% fail to execute successfully in a clean environment. This assessment is corroborated by a large-scale automated analysis that yields a consistent code availability rate of 26.8%. Further, it shows that approximately one-third of the papers with accessible code lack machine-readable environment specifications. The results in this paper indicate that reproducibility is not yet consistently achieved in quantum computing research. In response, we outline a set of practical recommendations that address the observed failure modes and illustrate how reproducibility can be improved in practice.
