@inbook{ccf5a5723dfd48acbd70453cd67b0362,
title = "Uncertainty quantification and stochastic modelling of photonic device from experimental data through polynomial chaos expansion",
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.",
keywords = "Generalized polynomial chaos (gPC), Integrated photonic, Stochastic process",
author = "Abi Waqas and Daniele Melati and Zarlish Mushtaq and Andrea Melloni",
note = "Publisher Copyright: {\textcopyright} 2018 SPIE.; Integrated Optics: Devices, Materials, and Technologies XXII 2018 ; Conference date: 29-01-2018 Through 01-02-2018",
year = "2018",
doi = "10.1117/12.2290540",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Garcia-Blanco, \{Sonia M.\} and Pavel Cheben",
booktitle = "Integrated Optics",
address = "United States",
}