TR2021-140
Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics
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- , "Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics", IEEE Photonics Conference (IPC), DOI: 10.1109/IPC48725.2021.9593086, October 2021, pp. 1-2.BibTeX TR2021-140 PDF
- @inproceedings{Li2021oct,
- author = {Li, Xinhao and Kojima, Keisuke and Brand, Matthew},
- title = {Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics},
- booktitle = {IEEE Photonics Conference (IPC)},
- year = 2021,
- pages = {1--2},
- month = oct,
- doi = {10.1109/IPC48725.2021.9593086},
- issn = {2575-274X},
- isbn = {978-1-6654-1601-6},
- url = {https://www.merl.com/publications/TR2021-140}
- }
- , "Predicting Long- and Variable-Distance Coupling Effects in Metasurface Optics", IEEE Photonics Conference (IPC), DOI: 10.1109/IPC48725.2021.9593086, October 2021, pp. 1-2.
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MERL Contact:
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Research Areas:
Applied Physics, Electronic and Photonic Devices, Machine Learning
Abstract:
A novel deep learning neural network architecture is proposed to predict the near electrical field produced by metasurface devices with long-distance coupling effects in large neighborhoods of nano-pillars. This reduces LPA-FDTD error by 60%.