Research Library

open-access-imgOpen AccessLanguage-controllable programmable metasurface empowered by large language models
Author(s)
Hu Shengguo,
Xu Jiawen,
Li Mingyi,
Cui Tie Jun,
Li Lianlin
Publication year2024
Publication title
nanophotonics
Resource typeJournals
PublisherDe Gruyter
Programmable metasurface has become a prominent tool in various areas including control, communication, computing, and so on, due to its unique capability in the electromagnetic (EM) manipulation. However, it is lack of the intelligence in the sense that it usually requires the manual intervention, and thus makes it hard to behavior as the human process. To endow the programmable metasurface with the intelligence, we here proposed the concept of the language-controllable programmable metasurface for autonomous EM manipulations by exploring the notable capability of large language models (LLMs) in attaining the human-like intelligence. We have established a proof-of-principle system of language-controllable programmable metasurface, where, for illustration, the programmable metasurface is designed to have 32 × 24 binary electronically controllable meta-atoms and work at around 5.5 GHz. In addition, we have constructed a visual-semantic map to facilitate the language-controllable EM manipulation in three-dimensional (3D) physical environments. We have experimentally demonstrated that our language-controllable programmable metasurface is capable of decomposing autonomously an ambiguous task of EM manipulation into a sequence of executable ones and implementing them individually in real-world indoor settings. We expect that the presented strategy could hold promising potential in pushing programmable metasurfaces towards human-level autonomous agents, which are capable of accomplishing the smart EM-involved multi-modality manipulations through self-directed planning and actions.
Keyword(s)programmable metasurface, large language models, EM manipulation
Language(s)English
SCImago Journal Rank2.717
H-Index61
eISSN2192-8614
pISSN2192-8606
DOI10.1515/nanoph-2023-0646

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