Probabilistic inverse design of metasurfaces using mixture density neural networks
Metasurfaces are planar sub-micron structures that can outperform traditional optical elements and miniaturize optical devices. Optimization-based inverse designs of metasurfaces often get trapped in a local minimum, and the inherent non-uniqueness property of the inverse problem plagues approaches...
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IOP Publishing
2024-01-01
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| Series: | JPhys Photonics |
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| Online Access: | https://doi.org/10.1088/2515-7647/ad9b82 |
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| author | Mahsa Torfeh Chia Wei Hsu |
| author_facet | Mahsa Torfeh Chia Wei Hsu |
| author_sort | Mahsa Torfeh |
| collection | DOAJ |
| description | Metasurfaces are planar sub-micron structures that can outperform traditional optical elements and miniaturize optical devices. Optimization-based inverse designs of metasurfaces often get trapped in a local minimum, and the inherent non-uniqueness property of the inverse problem plagues approaches based on conventional neural networks. Here, we use mixture density neural networks to overcome the non-uniqueness issue for the design of metasurfaces. Once trained, the mixture density network (MDN) can predict a probability distribution of different optimal structures given any desired property as the input, without resorting to an iterative local optimization. As an example, we use the MDN to design metasurfaces that project structured light patterns with varying fields of view. This approach enables an efficient and reliable inverse design of fabrication-ready metasurfaces with complex functionalities without getting trapped in local optima. |
| format | Article |
| id | doaj-art-29d27d2ecb7842079bbcf927579e7a7f |
| institution | OA Journals |
| issn | 2515-7647 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | JPhys Photonics |
| spelling | doaj-art-29d27d2ecb7842079bbcf927579e7a7f2025-08-20T02:36:53ZengIOP PublishingJPhys Photonics2515-76472024-01-017101500710.1088/2515-7647/ad9b82Probabilistic inverse design of metasurfaces using mixture density neural networksMahsa Torfeh0https://orcid.org/0009-0003-6782-9331Chia Wei Hsu1Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California , Los Angeles, CA 90089, United States of AmericaMing Hsieh Department of Electrical and Computer Engineering, University of Southern California , Los Angeles, CA 90089, United States of AmericaMetasurfaces are planar sub-micron structures that can outperform traditional optical elements and miniaturize optical devices. Optimization-based inverse designs of metasurfaces often get trapped in a local minimum, and the inherent non-uniqueness property of the inverse problem plagues approaches based on conventional neural networks. Here, we use mixture density neural networks to overcome the non-uniqueness issue for the design of metasurfaces. Once trained, the mixture density network (MDN) can predict a probability distribution of different optimal structures given any desired property as the input, without resorting to an iterative local optimization. As an example, we use the MDN to design metasurfaces that project structured light patterns with varying fields of view. This approach enables an efficient and reliable inverse design of fabrication-ready metasurfaces with complex functionalities without getting trapped in local optima.https://doi.org/10.1088/2515-7647/ad9b82Nanophotonicsmetasurfaceinverse designdeep neural networkmixture density networkstructured light |
| spellingShingle | Mahsa Torfeh Chia Wei Hsu Probabilistic inverse design of metasurfaces using mixture density neural networks JPhys Photonics Nanophotonics metasurface inverse design deep neural network mixture density network structured light |
| title | Probabilistic inverse design of metasurfaces using mixture density neural networks |
| title_full | Probabilistic inverse design of metasurfaces using mixture density neural networks |
| title_fullStr | Probabilistic inverse design of metasurfaces using mixture density neural networks |
| title_full_unstemmed | Probabilistic inverse design of metasurfaces using mixture density neural networks |
| title_short | Probabilistic inverse design of metasurfaces using mixture density neural networks |
| title_sort | probabilistic inverse design of metasurfaces using mixture density neural networks |
| topic | Nanophotonics metasurface inverse design deep neural network mixture density network structured light |
| url | https://doi.org/10.1088/2515-7647/ad9b82 |
| work_keys_str_mv | AT mahsatorfeh probabilisticinversedesignofmetasurfacesusingmixturedensityneuralnetworks AT chiaweihsu probabilisticinversedesignofmetasurfacesusingmixturedensityneuralnetworks |