Machine learning-based evaluation of performance of silicon nitride waveguide fabrication: Gradient-boosted forests for predicting propagation and bend excess losses
The propagation and bend excess loss characteristics of silicon nitride strip waveguides at an 850 nm wavelength were explored in this study. The aim was to optimize fabrication processes using machine learning, particularly gradient-boosted forests, to achieve low-loss photonic integrated circuits...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2024/19/epjconf_eosam2024_01008.pdf |
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