实践中的量子软件工程：用于量子认证的FPGA与人工智能集成
Quantum Software Engineering in Practice: FPGA and AI Integration for Quantum Certification
AI总结：
研究针对量子计算机认证挑战，提出遵循QSE原则的混合认证框架QAccCert，集成FPGA和人工智能技术，通过CHSH不等式在理想量子模拟中实现纠缠认证，经大语言模型引导优化，有效探索参数空间，为实际量子认证提供方法。
摘要：
量子软件工程（QSE）的出现，满足了对量子软件开发、运行和维护采用系统、规范且可量化方法的需求。在此背景下，量子计算机认证是一项重大挑战，即要验证量子设备在存在硬件缺陷、噪声和退相干的情况下仍能产生有效的纠缠态。本文提出了QAccCert，这是一个遵循QSE原则开发的混合认证框架，展示了如何将FPGA和人工智能等异构技术集成用于量子处理。该框架通过使用Qiskit AerSimulator在理想量子模拟中通过违反CHSH不等式来实现纠缠认证。通过大语言模型引导的优化，系统达到了理论最大值$2\sqrt{2}$的99.94%，证明了比随机搜索更有效地探索参数空间。这些模拟结果说明了QSE方法与战略技术互连相结合，可在未来工作中应用于实际的、可扩展的量子认证。本研究提供了系统量子软件开发的具体案例。
英文摘要：
The emergence of Quantum Software Engineering (QSE) responds to the need for systematic, disciplined, and quantifiable approaches to the development, operation, and maintenance of quantum software. Within this context, quantum computer certification represents a significant challenge: verifying that quantum devices produce valid entangled states despite hardware imperfections, noise, and decoherence. This paper presents QAccCert, a hybrid certification framework developed following QSE principles, demonstrating how heterogeneous technologies like FPGAs and Artificial Intelligence can be integrated for quantum processing. The framework implements entanglement certification through CHSH inequality violation in ideal quantum simulations using Qiskit AerSimulator. Through LLM-guided optimization, the system achieves 99.94% of the theoretical maximum of $2\sqrt{2}$, evidencing more efficient parameter space exploration than random search. These simulated results illustrate how QSE methodologies, combined with strategic technology interconnection, can be applied for practical and scalable quantum certification on real NISQ hardware in future work. This study provides a concrete case study of systematic quantum software development.
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