2022
DOI: 10.1016/j.jcp.2021.110807
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Efficient uncertainty propagation for photonics: Combining Implicit Semi-analog Monte Carlo (ISMC) and Monte Carlo generalised Polynomial Chaos (MC-gPC)

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Cited by 4 publications
(33 citation statements)
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References 54 publications
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“…This may be considered a drawback. But, on another hand, important computational gains obtained with MC-gPC have been observed on many (linear [1,3] or nonlinear [4,5,6,7]) applications. Its use allows performing studies (uncertainty propagation, sensitivity analysis etc.)…”
Section: Introductionmentioning
confidence: 99%
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“…This may be considered a drawback. But, on another hand, important computational gains obtained with MC-gPC have been observed on many (linear [1,3] or nonlinear [4,5,6,7]) applications. Its use allows performing studies (uncertainty propagation, sensitivity analysis etc.)…”
Section: Introductionmentioning
confidence: 99%
“…Its use allows performing studies (uncertainty propagation, sensitivity analysis etc.) which, up to now, were out of reach [1,7,6]. In this article, we are interested in the MC resolution of the gPC based reduced model of the uncertain linear transport equation ∂ t u(x, t, v, X) + v • ∇ x u(x, t, v, X) = − vσ t (x, v, X)u(x, t, v, X)…”
Section: Introductionmentioning
confidence: 99%
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