A Comprehensive Review of Large Language Models for Nanophotonics: From Surrogate Modeling to Autonomous Design
Metasurfaces have revolutionized the development of photonic devices by enabling unprecedented precision in light manipulation. However, their design processes are often constrained by computationally expensive simulations and complex high-dimensional design spaces. Although deep learning has accelerated the design process by serving as a surrogate model, it remains constrained by task-specific architectures and lacks universal reasoning capabilities. This review surveys how Large Language Models (LLMs) are adding semantic interfaces, code generation, and tool orchestration to established numerical nanophotonic workflows. We first outline the development from classical neural networks to ...
| Authors | Huanshu Zhang, Kegeng Tang, Lei Kang et al. |
|---|---|
| Primary category | physics.optics |
| Published | 18 August 2026 |
| Last updated at source | 24 September 2026 |
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