用自然语言让AI自动完成量子化学计算，无需专业背景。
El Agente: An Autonomous Agent for Quantum Chemistry
- 基于大模型的多智能体系统，可将自然语言指令转为化学计算流程。
- 在6个课程题和2个案例中平均成功率超87%，能自主调试错误。
- 适合化学研究者、学生及需要自动化计算的科研人员使用。
计算化学工具广泛用于研究化学现象，但其复杂性使非专家难以使用，甚至对专家也构成挑战。本文提出El Agente Q，一个基于大语言模型的多智能体系统，可根据自然语言用户指令动态生成并执行量子化学工作流。该系统采用新型分层记忆架构，支持灵活的任务分解、自适应工具选择、事后分析以及自主的文件处理与提交。在六个大学课程练习和两个案例研究中进行评估，表现出稳健的问题解决能力（平均任务成功率>87%），并通过实时调试实现自适应错误处理。系统还能支持更复杂的多步任务，同时通过详细的动作追踪日志保持透明性。这些能力为实现更自主、更易访问的量子化学研究奠定了基础。
原文摘要 · Abstract (English)
Computational chemistry tools are widely used to study the behaviour of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging >87% task success) and adaptive error handling through in situ debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry.
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