The reverse design of a tunable terahertz metasurface antenna based on a deep neural network

被引:2
|
作者
Dao, Ri-Na [1 ]
Qi, Li-Mei [1 ,2 ]
Hu, Kai-Xiang [3 ]
Yang, Jun-Li [3 ]
Liu, Zi-Yu [1 ]
Wu, Li-Qin [4 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China
[2] Shandong Normal Univ, Collaborat Innovat Ctr Light Manipulat & Applicat, Jinan, Peoples R China
[3] Beijing Univ Posts & Telecommun, Int Sch, Beijing 100876, Peoples R China
[4] Beijing Acad Sci & Technol, Inst Radiat Technol, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
deep learning; metasurface; reverse design; terahertz antenna; INVERSE DESIGN; ABSORBER; OPTICS;
D O I
10.1002/mop.33471
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The reverse design of a tunable terahertz metasurface antenna is proposed based on the deep neural network (DNN). To obtain the tunable properties of the terahertz antenna, the phase-changed material vanadium dioxide (VO2) is introduced by controlling the voltage without changing the structures of the metasurface antenna. To improve the efficiency and accuracy of the terahertz antenna, the DNN is used to establish the relationship of amplitude and phase for the antenna unit. The prediction errors are below 10%. The radiation direction of the antenna can be changed from 0 degrees to 52 degrees by the VO2 with different states. The prediction error of angle is only 1 degrees difference from the theoretical calculation. This reverse design method can be extended to other metasurface devices with improved efficiency and accuracy.
引用
收藏
页码:264 / 272
页数:9
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