Wafer-Level Characterization of Silicon Nitride CWDM (De)Multiplexers Using Bayesian Inference

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Wafer-Level Characterization of Silicon Nitride CWDM (De)Multiplexers Using Bayesian Inference
Title:
Wafer-Level Characterization of Silicon Nitride CWDM (De)Multiplexers Using Bayesian Inference
Other Titles:
IEEE Photonics Technology Letters
Publication Date:
25 June 2020
Citation:
Ong, J. R., Guo, T. X., Ang, T. Y. L., Lim, S. T., Wang, H., & Png, C. E. (2020). Wafer-Level Characterization of Silicon Nitride CWDM (De)Multiplexers Using Bayesian Inference. IEEE Photonics Technology Letters, 32(15), 917–920. doi:10.1109/lpt.2020.3004850
Abstract:
A cascaded Mach-Zehnder interferometer based filter for coarse wavelength (de)multiplexing (CWDM) at the O-band is fabricated and tested on a silicon nitride on SOI platform. We characterize the chip-to-chip performance variability of the filter devices on a wafer. Using the optical measurement data, we apply Bayesian inference methods to estimate the waveguide geometery parameters and also quantify the uncertainty of the estimates.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR-NTU-SUTD AI Partnership - A*STAR-NTU-SUTD AI Partnership Grant
Grant Reference no. : RGANS1901
Description:
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISSN:
1041-1135
1941-0174
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