| DOI | Resolve DOI: https://doi.org/10.1117/12.2290540 |
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| Author | Search for: Waqas, Abi; Search for: Melati, Daniele1; Search for: Mushtaq, Zarlish; Search for: Melloni, Andrea I. |
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| Editor | Search for: García-Blanco, Sonia M.; Search for: Cheben, PavelORCID identifier: https://orcid.org/0000-0003-4232-9130 |
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| Name affiliation | - National Research Council of Canada. Advanced Electronics and Photonics
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| Format | Text, Article |
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| Conference | Integrated Optics: Devices, Materials, and Technologies XXII, January 27 - February 1, 2018, San Francisco, United States |
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| Subject | integrated photonic; generalized polynomial chaos (gPC); stochastic process |
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| 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. |
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| Publication date | 2018-03-01 |
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| Publisher | SPIE |
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| In | |
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| Series | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 23002831 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction |
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| Record identifier | 753e16f4-1318-4cc9-ac16-7560cddebdb9 |
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| Record created | 2018-03-08 |
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| Record modified | 2020-03-16 |
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