@Article{         Chauviere_2006aa,
  abstract      = {We discuss computationally efficient ways of accounting for the impact of uncertainty, e.g., lack of detailed knowledge about sources, materials, shapes, etc., in computational time-domain electromagnetics. In contrast to classic statistical Monte Carlo--based methods, we explore a probabilistic approach based on high-order accurate expansions of general stochastic processes. We show this to be highly efficient and accurate on both one- and two-dimensional examples, enabling the computation of global sensitivities of measures of interest, e.g., radar-cross-sections (RCS) in scattering applications, for a variety of types of uncertainties.},
  author        = {Chauvière, Cédric and Hesthaven, Jan S. and Lurati, Laura},
  doi           = {10.1137/040621673},
  file          = {Chauviere_2006aa.pdf},
  issn          = {1064-8275},
  journal       = {SIAM Journal on Scientific Computing},
  keywords      = {maxwell,uncertainty,gpc},
  langid        = {english},
  number        = {2},
  pages         = {751–-775},
  title         = {Computational Modeling of Uncertainty in Time-Domain Electromagnetics},
  volume        = {28},
  year          = {2006},
  shortjournal  = {SIAM J. Sci. Comput.}
}

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