Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive Indexes
In this study, an artificial neural network that can predict the band structure of 2-D photonic crystals is developed. Three kinds of photonic crystals in a square lattice, triangular lattice, and honeycomb lattice and two kinds of materials with different refractive indices are investigated. Using...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/8/1777 |
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| author | Fu-Li Hsiao Hsin-Feng Lee Su-Chao Wang Yu-Ming Weng Ying-Pin Tsai |
| author_facet | Fu-Li Hsiao Hsin-Feng Lee Su-Chao Wang Yu-Ming Weng Ying-Pin Tsai |
| author_sort | Fu-Li Hsiao |
| collection | DOAJ |
| description | In this study, an artificial neural network that can predict the band structure of 2-D photonic crystals is developed. Three kinds of photonic crystals in a square lattice, triangular lattice, and honeycomb lattice and two kinds of materials with different refractive indices are investigated. Using the length of the wave vectors in the reduced Brillouin zone, band number, r/a ratio, and the refractive indices as the dataset, the desired ANN is trained to predict the eigenfrequencies of the photonic modes and depict the photonic band structures with a correlation coefficient greater than 0.99. By increasing the number of neurons in the hidden layer, the correlation coefficient can be further increased over 0.999. |
| first_indexed | 2024-03-11T05:04:50Z |
| format | Article |
| id | doaj.art-2bec20e113bc4a5ab6fc0c6be11f9f9e |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T05:04:50Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-2bec20e113bc4a5ab6fc0c6be11f9f9e2023-11-17T19:00:45ZengMDPI AGElectronics2079-92922023-04-01128177710.3390/electronics12081777Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive IndexesFu-Li Hsiao0Hsin-Feng Lee1Su-Chao Wang2Yu-Ming Weng3Ying-Pin Tsai4Institute of Photonics, National Changhua University of Education, Changhua 50007, TaiwanInstitute of Photonics, National Changhua University of Education, Changhua 50007, TaiwanInstitute of Photonics, National Changhua University of Education, Changhua 50007, TaiwanInstitute of Photonics, National Changhua University of Education, Changhua 50007, TaiwanInstitute of Imaging and Biomedical Photonics, College of Photonics, National Yang Ming Chiao Tung University, Tainan 71150, TaiwanIn this study, an artificial neural network that can predict the band structure of 2-D photonic crystals is developed. Three kinds of photonic crystals in a square lattice, triangular lattice, and honeycomb lattice and two kinds of materials with different refractive indices are investigated. Using the length of the wave vectors in the reduced Brillouin zone, band number, r/a ratio, and the refractive indices as the dataset, the desired ANN is trained to predict the eigenfrequencies of the photonic modes and depict the photonic band structures with a correlation coefficient greater than 0.99. By increasing the number of neurons in the hidden layer, the correlation coefficient can be further increased over 0.999.https://www.mdpi.com/2079-9292/12/8/1777photonic crystalartificial neural networkband structure |
| spellingShingle | Fu-Li Hsiao Hsin-Feng Lee Su-Chao Wang Yu-Ming Weng Ying-Pin Tsai Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive Indexes Electronics photonic crystal artificial neural network band structure |
| title | Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive Indexes |
| title_full | Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive Indexes |
| title_fullStr | Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive Indexes |
| title_full_unstemmed | Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive Indexes |
| title_short | Artificial Neural Network for Photonic Crystal Band Structure Prediction in Different Geometric Parameters and Refractive Indexes |
| title_sort | artificial neural network for photonic crystal band structure prediction in different geometric parameters and refractive indexes |
| topic | photonic crystal artificial neural network band structure |
| url | https://www.mdpi.com/2079-9292/12/8/1777 |
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