Uncertainty quantification and stochastic modelling of photonic device from experimental data through polynomial chaos expansion

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1117/12.2290540
AuthorSearch for: ; Search for: 1 ; Search for: ; Search for:
EditorSearch for: García-Blanco, Sonia M.; Search for: Cheben, Pavel
Name affiliation
  1. National Research Council Canada. Advanced Electronics and Photonics
FormatText
TypeArticle
Proceedings titleIntegrated Optics: Devices, Materials, and Technologies XXII
Series titleProceedings of SPIE; no. 10535
ConferenceIntegrated Optics: Devices, Materials, and Technologies XXII, January 27 - February 1, 2018, San Francisco, United States
ISSN0277-786X
ISBN9781510615557
9781510615564
Article number105351A
Pages# of pages: 6
Subjectintegrated photonic; generalized polynomial chaos (gPC); stochastic process
Abstract
Unavoidable statistical variations in fabrication processes have a strong effect on the functionality of fabricated photonic circuits and on fabrication yield. It is hence essential to measure and consider these uncertainties during the design in order to predict the statistical behavior of the realized circuits. Also, during the mass production of photonic integrated circuits, the experimental evaluation of circuits’ desired quantity of interest in the presence of fabrication error can be crucial. In this paper we proposed the use of generalized polynomial chaos method to estimate the statistical properties of a circuit from a reduced number of experimental data whilst achieving good accuracy comparable to those obtained by Monte Carlo.
Publication date
PublisherSPIE
LanguageEnglish
Peer reviewedYes
NPARC number23002831
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Record identifier753e16f4-1318-4cc9-ac16-7560cddebdb9
Record created2018-03-08
Record modified2018-10-31
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