Innovation in nanophotonics currently relies on human experts who synergize specialized knowledge in photonics and coding with simulation and optimization algorithms, entailing design cycles that are time-consuming, computationally demanding, and frequently suboptimal. We introduce MetaChat, a multi-agentic design framework that can translate semantically described photonic design goals into high-performance, freeform device layouts in an automated, nearly real-time manner. Multi-step reasoning is enabled by our Agentic Iterative Monologue (AIM) paradigm, which coherently interfaces agents with code-based tools, other specialized agents, and human designers. Design acceleration is facilitated by Feature-wise Linear Modulation-conditioned Maxwell surrogate solvers that support the generalized evaluation of metasurface structures. We use freeform dielectric metasurfaces as a model system and demonstrate with MetaChat the design of multi-objective, multi-wavelength metasurfaces orders of magnitude faster than conventional methods. These concepts present a scientific computing blueprint for utilizing specialist design agents, surrogate solvers, and human interactions to drive multi-physics innovation and discovery.

翻译：当前纳米光子学领域的创新依赖于人类专家，他们需要将光子学与编码的专业知识同仿真及优化算法相结合，这导致设计周期耗时、计算需求高且常常无法达到最优。我们提出了MetaChat，一个多智能体设计框架，能够将语义描述的光子设计目标自动、近乎实时地转化为高性能的自由形状器件布局。多步推理通过我们提出的智能体迭代独白范式实现，该范式能协调地将智能体与基于代码的工具、其他专业智能体以及人类设计师相连接。设计加速得益于特征线性调制条件麦克斯韦代理求解器的支持，该求解器能够对超表面结构进行广义评估。我们以自由形状介电超表面作为模型系统，并通过MetaChat展示了多目标、多波长超表面的设计，其速度比传统方法快数个数量级。这些概念为利用专业设计智能体、代理求解器以及人机交互来推动多物理场创新与发现，提供了一个科学计算的蓝图。