Iterative optimization of photonic crystal nanocavity designs by using deep neural networks
Devices based on two-dimensional photonic-crystal nanocavities, which are defined by their air hole patterns, usually require a high quality (Q) factor to achieve high performance. We demonstrate that hole patterns with very high Q factors can be efficiently found by the iteration procedure consisti...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
De Gruyter
2019-11-01
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Series: | Nanophotonics |
Subjects: | |
Online Access: | https://doi.org/10.1515/nanoph-2019-0308 |