Abstract
Finite-difference time-domain (FDTD) algorithms are affected by numerical artifacts and noise. In order to obtain better results we propose the use of the principal component analysis based on multivariate statistical techniques. It allows a straightforward discrimination between the numerical noise and the actual electromagnetic field distributions, and the quantitative estimation of their respective contributions. Besides, the FDTD results can be filtered to clean the effect of the noise. The method has been applied successfully to two dimensional simulations: propagation of a pulse in vacuum using total field-scattered field techniques, and mode computation in a two-dimensional photonic crystal. In this last case, PCA has revealed hidden electromagnetic structures related to actual modes of the photonic crystal.
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