volume | PIER Journals

Abstract

Compelling evidence suggests that the interaction between electromagnetic metasurfaces and deep learning gives rise to the proliferation of intelligent metasurfaces in the past decade. In general, deep learning offers a transformative force to reform the design and working style of metasurfaces. A majority of the inverse-design literature announce that, given a user-defined input, the pre-trained deep learning models can quickly output the metasurface candidates with high fidelity. However, they largely ignore an important fact, that is, the practical input is always semi-known. In this work, we introduce a generation-elimination network that is robust to semi-known input and information pollution. The network is composed of a generative network to generate a number of possible answers and then a discriminative network to eliminate suboptimal answers. We benchmark the feasibility via two scenes, the on-demand metasurface design of the reflection spectra and the far-field pattern. In the microwave experiment, we fabricated and measured the reconfigurable metasurfaces to automatically meet the semi-known beam steering requirement that widely exist in wireless communication. Our work for the first time answers the question of how to cope with semi-known input, which is ubiquitous in a panoply of real-world applications, such as imaging, sensing, and communication across noisy environment.

1. Liu, Dong, Yue Li, Jianping Lin, Houqiang Li, and Feng Wu, "Deep learning-based video coding: A review and a case study," ACM Computing Surveys, Vol. 53, No. 1, 1-35, Feb. 2020.
doi:10.1145/3368405 Google Scholar

2. Wang, Zhihao, Jian Chen, and Steven C. H. Hoi, "Deep learning for image super-resolution: A survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, No. 10, 3365-3387, Oct. 2021.
doi:10.1109/TPAMI.2020.2982166 Google Scholar

3. Purwins, Hendrik, Bo Li, Tuomas Virtanen, Jan Schlueter, Shuo-Yiin Chang, and Tara Sainath, "Deep learning for audio signal processing," IEEE Journal of Selected Topics in Signal Processing, Vol. 13, No. 2, 206-219, May 2019.
doi:10.1109/JSTSP.2019.2908700 Google Scholar

4. Qian, Chao, Yi Yang, Yifei Hua, Chan Wang, Xiao Lin, Tong Cai, Dexin Ye, Erping Li, Ido Kaminer, and Hongsheng Chen, "Breaking the fundamental scattering limit with gain metasurfaces," Nature Communications, Vol. 13, No. 1, 4383, Jul. 2022.
doi:10.1038/s41467-022-32067-9 Google Scholar

5. Cai, Tong, Bin Zheng, Jing Lou, Lian Shen, Yihao Yang, Shiwei Tang, Erping Li, Chao Qian, and Hongsheng Chen, "Experimental realization of a superdispersion-enabled ultrabroadband terahertz cloak," Advanced Materials, Vol. 34, No. 47, 2205053, Nov. 2022.
doi:10.1002/adma.202205053 Google Scholar

6. Jia, Yuetian, Chao Qian, Zhixiang Fan, Tong Cai, Er-Ping Li, and Hongsheng Chen, "A knowledge-inherited learning for intelligent metasurface design and assembly," Light Science & Applications, Vol. 12, No. 1, 82, Mar. 2023.
doi:10.1038/s41377-023-01131-4 Google Scholar

7. He, Qiong, Shulin Sun, and Lei Zhou, "Tunable/Reconfigurable metasurfaces: physics and applications," Research, Vol. 2019, 1849272, 2019. Google Scholar

8. Huang, Cheng, Changlei Zhang, Jianing Yang, Bo Sun, Bo Zhao, and Xiangang Luo, "Reconfigurable metasurface for multifunctional control of electromagnetic waves," Advanced Optical Materials, Vol. 5, No. 22, 1700485, Nov. 2017.
doi:10.1002/adom.201700485 Google Scholar

9. Chen, Jieting, Chao Qian, Jie Zhang, Yuetian Jia, and Hongsheng Chen, "Correlating metasurface spectra with a generation-elimination framework," Nature Communications, Vol. 14, No. 1, 4872, Aug. 2023.
doi:10.1038/s41467-023-40619-w Google Scholar

10. Wang, Zhedong, Min Chen, Chao Qian, Zhixiang Fan, Huaping Wang, and Hongsheng Chen, "Reconfigurable matrix multiplier with on-site reinforcement learning," Optics Letters, Vol. 47, No. 22, 5897-5900, Nov. 2022.
doi:10.1364/OL.472729 Google Scholar

11. Zhang, Jie, Chao Qian, Jieting Chen, Bei Wu, and Hongsheng Chen, "Uncertainty qualification for metasurface design with amendatory bayesian network," Laser & Photonics Reviews, Vol. 17, No. 5, 2200807, May 2023.
doi:10.1002/lpor.202200807 Google Scholar

12. Khatib, Omar, Simiao Ren, Jordan Malof, and Willie J. Padilla, "Deep learning the electromagnetic properties of metamaterials - A comprehensive review," Advanced Functional Materials, Vol. 31, 2101748, Aug. 2021.
doi:10.1002/adfm.202101748 Google Scholar

13. Ramprasad, Rampi, Rohit Batra, Ghanshyam Pilania, Arun Mannodi-Kanakkithodi, and Chiho Kim, "Machine learning in materials informatics: Recent applications and prospects," Npj Computational Materials, Vol. 3, 54, Dec. 2017.
doi:10.1038/s41524-017-0056-5 Google Scholar

14. Jia, Yuetian, Chao Qian, Zhixiang Fan, Yinzhang Ding, Zhedong Wang, Dengpan Wang, Er-Ping Li, Bin Zheng, Tong Cai, and Hongsheng Chen, "In situ customized illusion enabled by global metasurface reconstruction," Advanced Functional Materials, Vol. 32, No. 19, 2109331, May 2022.
doi:10.1002/adfm.202109331 Google Scholar

15. Fan, Z., et al. "Transfer-learning-assisted inverse metasurface design with 30% data savings," Phys. Rev. Appl., Vol. 18, 024022, 2022.
doi:10.1103/PhysRevApplied.18.024022 Google Scholar

16. Fan, Zhixiang, Chao Qian, Yuetian Jia, Zhedong Wang, Yinzhang Ding, Dengpan Wang, Longwei Tian, Erping Li, Tong Cai, Bin Zheng, Ido Kaminer, and Hongsheng Chen, "Homeostatic neuro-metasurfaces for dynamic wireless channel management," Science Advances, Vol. 8, No. 27, eabn7905, Jul. 2022.
doi:10.1126/sciadv.abn7905 Google Scholar

17. Gao, Li, Xiaozhong Li, Dianjing Liu, Lianhui Wang, and Zongfu Yu, "A bidirectional deep neural network for accurate silicon color design," Advanced Materials, Vol. 31, No. 51, 1905467, Dec. 2019.
doi:10.1002/adma.201905467 Google Scholar

18. Qian, Chao, Zhedong Wang, Haoliang Qian, Tong Cai, Bin Zheng, Xiao Lin, Yichen Shen, Ido Kaminer, Erping Li, and Hongsheng Chen, "Dynamic recognition and mirage using neuro-metamaterials," Nature Communications, Vol. 13, No. 1, 2694, May 2022.
doi:10.1038/s41467-022-30377-6 Google Scholar

19. Jiang, Jiaqi and Jonathan A. Fan, "Global optimization of dielectric metasurfaces using a physics-driven neural network," Nano Letters, Vol. 19, No. 8, 5366-5372, Aug. 2019.
doi:10.1021/acs.nanolett.9b01857 Google Scholar

20. Wiecha, Peter R. and Otto L. Muskens, "Deep learning meets nanophotonics: A generalized accurate predictor for near fields and far fields of arbitrary 3D nanostructures," Nano Letters, Vol. 20, No. 1, 329-338, Jan. 2020.
doi:10.1021/acs.nanolett.9b03971 Google Scholar

21. Qian, Chao, Bin Zheng, Yichen Shen, Li Jing, Erping Li, Lian Shen, and Hongsheng Chen, "Deep-learning-enabled self-adaptive microwave cloak without human intervention," Nature Photonics, Vol. 14, No. 6, 383, Jun. 2020.
doi:10.1038/s41566-020-0604-2 Google Scholar

22. Wang, Zhedong, Chao Qian, Tong Cai, Longwei Tian, Zhixiang Fan, Jian Liu, Yichen Shen, Li Jing, Jianming Jin, Er-Ping Li, Bin Zheng, and Hongsheng Chen, "Demonstration of spider-eyes-like intelligent antennas for dynamically perceiving incoming waves," Advanced Intelligent Systems, Vol. 3, No. 9, 2100066, Sep. 2021.
doi:10.1002/aisy.202100066 Google Scholar

23. Raccuglia, Paul, Katherine C. Elbert, Philip D. F. Adler, Casey Falk, Malia B. Wenny, Aurelio Mollo, Matthias Zeller, Sorelle A. Friedler, Joshua Schrier, and Alexander J. Norquist, "Machine-learning-assisted materials discovery using failed experiments," Nature, Vol. 533, No. 7601, 73-76, May 2016.
doi:10.1038/nature17439 Google Scholar

24. Qian, Chao, Xiao Lin, Xiaobin Lin, Jian Xu, Yang Sun, Erping Li, Baile Zhang, and Hongsheng Chen, "Performing optical logic operations by a diffractive neural network," Light Science & Applications, Vol. 9, No. 1, 59, Apr. 2020.
doi:10.1038/s41377-020-0303-2 Google Scholar

25. Zhang, Jie, Chao Qian, Zhixiang Fan, Jieting Chen, Erping Li, Jianming Jin, and Hongsheng Chen, "Heterogeneous transfer-learning-enabled diverse metasurface design," Advanced Optical Materials, Vol. 10, No. 17, 2200748, Sep. 2022.
doi:10.1002/adom.202200748 Google Scholar

26. Wu, Nanxuan, Yuetian Jia, Chao Qian, and Hongsheng Chen, "Pushing the limits of metasurface cloak using global inverse design," Advanced Optical Materials, Vol. 11, No. 7, 2202130, Apr. 2023.
doi:10.1002/adom.202202130 Google Scholar

27. Zhu, Xiaoyue, Chao Qian, Yuetian Jia, Jieting Chen, Yuan Fang, Zhixiang Fan, Jie Zhang, Dongdong Li, Reza Abdi-Ghaleh, and Hongsheng Chen, "Realization of index modulation with intelligent spatiotemporal metasurfaces," Advanced Intelligent Systems, Vol. 5, No. 7, 2300065, Jul. 2023.
doi:10.1002/aisy.202300065 Google Scholar

28. Kingma, D. P. and M. Welling, "Auto-encoding variational bayes," http://arxiv.org/abs/1312.6114, 2014.

29. Sohn, Kihyuk, Xinchen Yan, and Honglak Lee, "Learning structured output representation using deep conditional generative models," Advances in Neural Information Processing Systems (NIPS 2015), Vol. 28, Montreal, Canada, Dec. 2015.

30. Qian, Chao and Hongsheng Chen, "A perspective on the next generation of invisibility cloaks-intelligent cloaks," Applied Physics Letters, Vol. 118, No. 18, 180501, May 2021.
doi:10.1063/5.0049748 Google Scholar

31. Zhen, Zheng, Chao Qian, Yuetian Jia, Zhixiang Fan, Ran Hao, Tong Cai, Bin Zheng, Hongsheng Chen, and Erping Li, "Realizing transmitted metasurface cloak by a tandem neural network," Photonics Research, Vol. 9, No. 5, B229-B235, May 2021.
doi:10.1364/PRJ.418445 Google Scholar

32. Wu, Q. and R. Zhang, "Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming," IEEE Trans. Wireless Commun., Vol. 18, 5394-5409, 2019.
doi:10.1109/TWC.2019.2936025 Google Scholar

33. Basar, Ertugrul, "Reconfigurable intelligent surface-based index modulation: A new beyond MIMO paradigm for 6G," IEEE Transactions on Communications, Vol. 68, No. 5, 3187-3196, May 2020.
doi:10.1109/TCOMM.2020.2971486 Google Scholar

34. Hu, Q., et al. "An intelligent programmable omni-metasurface," Laser Photon. Rev., Vol. 16, 2100718, 2022.
doi:10.1002/lpor.202100718 Google Scholar

35. Lu, Huan, Jiwei Zhao, Bin Zheng, Chao Qian, Tong Cai, Erping Li, and Hongsheng Chen, "Eye accommodation-inspired neuro-metasurface focusing," Nature Communications, Vol. 14, No. 1, 2023. Google Scholar

36. Zhang, K., et al. "Ultrasensitive self-driven terahertz photodetectors based on low-energy type-II dirac fermions and related van der Waals heterojunctions," Small, Vol. 19, 2205329, 2023.
doi:10.1002/smll.202205329 Google Scholar

37. Hu, Z. and et al., "Terahertz nonlinear hall rectifiers based on spin-polarized topological electronic states in 1T-CoTe2," Advanced Materials, Vol. 35, 2209557, 2023.
doi:10.1002/adma.202209557 Google Scholar

38. Rizza, Carlo, Debasis Dutta, Barun Ghosh, Francesca Alessandro, Chia-Nung Kuo, Chin Shan Lue, Lorenzo S. Caputi, Arun Bansil, Vincenzo Galdi, Amit Agarwal, Antonio Politano, and Anna Cupolillo, "Extreme optical anisotropy in the type-II dirac semimetal NiTe2 for applications to nanophotonics," ACS Applied Nano Materials, Vol. 5, No. 12, 18531-18536, Dec. 2022.
doi:10.1021/acsanm.2c04340 Google Scholar

39. Daws, Sawsan, Parth Kotak, Chia-Nung Kuo, Chin Shan Lue, Antonio Politano, and Caterina Lamuta, "Platinum diselenide PtSe2: An ambient-stable material for flexible electronics," Materials Science and Engineering B-Advanced Functional Solid-State Materials, Vol. 283, 115824, Sep. 2022. Google Scholar

40. Vobornik, Ivana, Anan Bari Sarkar, Libo Zhang, Danil W. Boukhvalov, Barun Ghosh, Lesia Piliai, Chia-Nung Kuo, Debashis Mondal, Jun Fujii, Chin Shan Lue, Mykhailo Vorokhta, Huaizhong Xing, Lin Wang, Amit Agarwal, and Antonio Politano, "Kitkaite nitese, an ambient-stable layered dirac semimetal with low-energy type-ii fermions with application capabilities in spintronics and optoelectronics," Advanced Functional Materials, Vol. 31, No. 52, 2106101, Dec. 2021.
doi:10.1002/adfm.202106101 Google Scholar

41. Faenzi, M., et al. "Metasurface antennas: New models, applications and realizations," Sci. Rep., Vol. 9, 10178, 2019.
doi:10.1038/s41598-019-46522-z Google Scholar

42. Badawe, M. E., T. S. Almoneef, and O. M. Ramahi, "A true metasurface antenna," Sci. Rep., Vol. 6, 19268, 2016.
doi:10.1038/srep19268 Google Scholar

43. Tan, Q., C. Qian, T. Cai, B. Zheng, and H. Chen, "Solving multivariable equations with tandem metamaterial kernels," Progress In Electromagnetics Research, Vol. 175, 139-147, 2022.
doi:10.2528/PIER22060601 Google Scholar

44. Shou, Y., Y. Feng, Y. Zhang, H. Chen, and H. Qian, "Deep learning approach based optical edge detection using ENZ layers," Progress In Electromagnetics Research, Vol. 175, 81-89, 2022.
doi:10.2528/PIER22061403 Google Scholar

45. Xie, H., T. Hu, Z. Wang, Y. Yang, X. Hu, W. Qi, and H. Liu, "A physics-based HIE-FDTD method for electromagnetic modeling of multi-band frequency selective surface," Progress In Electromagnetics Research, Vol. 173, 129-140, 2022.
doi:10.2528/PIER22012103 Google Scholar

Dr. Pujing Lin

Professor Chao Qian

Dr. Jie Zhang

Dr. Jieting Chen

Dr. Xiaoyue Zhu

Dr. Zhedong Wang

Dr. Jiangtao Huangfu

Professor Hongsheng Chen