El Agente Quntur：一种用于量子化学研究的协作代理
El Agente Quntur: A research collaborator agent for quantum chemistry
AI总结：
本文提出El Agente Quntur，一种多代理AI系统，旨在通过推理驱动决策和指导深度研究，提升量子化学计算工具的可访问性与实用性。
摘要：
量子化学是化学、材料科学、计算生物学等领域的基础工具。尽管其强大，但实际应用仍受限于方法复杂性、软件异质性和结果解释需求。为弥合这些工具的可及性差距并扩展至更广泛背景的化学家，我们引入El Agente Quntur，一种分层、多代理AI系统，不仅作为自动化工具，更作为计算量子化学的研究协作者。Quntur遵循三个主要策略：i) 用推理驱动决策取代硬编码过程策略；ii) 构建通用且可组合的动作以促进泛化和效率；iii) 实现指导深度研究以整合跨学科的抽象量子化学推理及软件内部逻辑与语法的理解。尽管在ORCA中实现，这些设计原则适用于一般研究代理，并可扩展至其他量子化学包。Quntur支持ORCA 6.0中所有计算，并通过软件文档和科学文献进行推理，以规划、执行、适应和分析硅化学实验，遵循最佳实践。我们讨论了计算化学中研究级代理系统的进展和当前瓶颈，并概述了向完全自主的端到端计算化学研究代理的路线图。
英文摘要：
Quantum chemistry is a foundational enabling tool for the fields of chemistry, materials science, computational biology and others. Despite of its power, the practical application of quantum chemistry simulations remains in the hands of qualified experts due to methodological complexity, software heterogeneity, and the need for informed interpretation of results. To bridge the accessibility gap for these tools and expand their reach to chemists with broader backgrounds, we introduce El Agente Quntur, a hierarchical, multi-agent AI system designed to operate not merely as an automation tool but as a research collaborator for computational quantum chemistry. Quntur was designed following three main strategies: i) elimination of hard-coded procedural policies in favour of reasoning-driven decisions, ii) construction of general and composable actions that facilitate generalization and efficiency, and iii) implementation of guided deep research to integrate abstract quantum-chemical reasoning across subdisciplines and a detailed understanding of the software's internal logic and syntax. Although instantiated in ORCA, these design principles are applicable to research agents more generally and easily expandable to additional quantum chemistry packages and beyond. Quntur supports the full range of calculations available in ORCA 6.0 and reasons over software documentation and scientific literature to plan, execute, adapt, and analyze in silico chemistry experiments following best practices. We discuss the advances and current bottlenecks in agentic systems operating at the research level in computational chemistry, and outline a roadmap toward a fully autonomous end-to-end computational chemistry research agent.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
