Abstract
We propose a method to analyze the performance variability caused by fabrication uncertainty in photonic circuits with a large number of correlated parameters. By combining a sparse polynomial chaos expansion model with dimensionality reduction in the form of Karhunen-Loève transform and principal component analysis, we demonstrate the stochastic analysis of the transfer function of cascaded Mach-Zehnder interferometers with up to 38 correlated uncertain parameters.
| Original language | English |
|---|---|
| Article number | 9417609 |
| Pages (from-to) | 4737-4744 |
| Number of pages | 8 |
| Journal | Journal of Lightwave Technology |
| Volume | 39 |
| Issue number | 14 |
| DOIs | |
| Publication status | Published - 15 Jul 2021 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Correlated manufacturing variability
- Karhunen-Loève transform
- performance prediction
- photonic devices
- polynomial chaos
- principal component analysis
- process variations
- silicon photonics
- uncertainty quantification
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