{"ID":2828723,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.12888","arxiv_id":"2512.12888","title":"Meta-GPT: Decoding the Metasurface Genome with Generative Artificial Intelligence","abstract":"Advancing artificial intelligence for physical sciences requires representations that are both interpretable and compatible with the underlying laws of nature. We introduce METASTRINGS, a symbolic language for photonics that expresses nanostructures as textual sequences encoding materials, geometries, and lattice configurations. Analogous to molecular textual representations in chemistry, METASTRINGS provides a framework connecting human interpretability with computational design by capturing the structural hierarchy of photonic metasurfaces. Building on this representation, we develop Meta-GPT, a foundation transformer model trained on METASTRINGS and finetuned with physics-informed supervised, reinforcement, and chain-of-thought learning. Across various design tasks, the model achieves \u003c3% mean-squared spectral error and maintains \u003e98% syntactic validity, generating diverse metasurface prototypes whose experimentally measured optical responses match their target spectra. These results demonstrate that Meta-GPT can learn the compositional rules of light-matter interactions through METASTRINGS, laying a rigorous foundation for AI-driven photonics and representing an important step toward a metasurface genome project.","short_abstract":"Advancing artificial intelligence for physical sciences requires representations that are both interpretable and compatible with the underlying laws of nature. We introduce METASTRINGS, a symbolic language for photonics that expresses nanostructures as textual sequences encoding materials, geometries, and lattice confi...","url_abs":"https://arxiv.org/abs/2512.12888","url_pdf":"https://arxiv.org/pdf/2512.12888v1","authors":"[\"David Dang\",\"Stuart Love\",\"Meena Salib\",\"Quynh Dang\",\"Samuel Rothfarb\",\"Mysk Alnatour\",\"Andrew Salij\",\"Hou-Tong Chen\",\"Ho Wai\",\"Lee\",\"Wilton J. M. Kort-Kamp\"]","published":"2025-12-15T00:09:14Z","proceeding":"physics.optics","tasks":"[\"physics.optics\",\"cs.AI\",\"cs.CL\",\"cs.LG\"]","methods":"[\"Transformer\"]","has_code":false}