量子计算与AI融合，推动工程科学自动化新范式。
Quantum Computing and AI: Perspectives on Advanced Automation in Science and Engineering
- 提出量子CAE框架，用量子算法优化工程设计。
- 案例验证其在组合优化问题中的可行性。
- 适合关注量子智能协同的科研与工程人员。
人工智能与量子计算的进展正加速科学与工程过程的自动化，重塑研究方法。本文对比科学自动化与成熟的计算机辅助工程（CAE）实践，提出量子CAE框架，利用量子算法在工程设计中实现模拟、优化与机器学习。通过组合优化问题的案例研究展示其实用性。进一步讨论向更高自动化水平演进的路径，强调擅长量子算法设计的专用AI代理的关键作用。量子计算与AI的融合引发关于人机协同动态的深层思考，预示自动化发现与创新的变革未来。
原文摘要 · Abstract (English)
Recent advances in artificial intelligence (AI) and quantum computing are accelerating automation in scientific and engineering processes, fundamentally reshaping research methodologies. This perspective highlights parallels between scientific automation and established Computer-Aided Engineering (CAE) practices, introducing Quantum CAE as a framework that leverages quantum algorithms for simulation, optimization, and machine learning within engineering design. Practical implementations of Quantum CAE are illustrated through case studies for combinatorial optimization problems. Further discussions include advancements toward higher automation levels, highlighting the critical role of specialized AI agents proficient in quantum algorithm design. The integration of quantum computing with AI raises significant questions about the collaborative dynamics among human scientists and engineers, AI systems, and quantum computational resources, underscoring a transformative future for automated discovery and innovation.
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