López Alonso, José ManuelRico García, José MaríaAlda Serrano, Javier2023-06-202023-06-2020061012-5566https://hdl.handle.net/20.500.14352/51930Accesible a texto completo en la web del editor.Finite-Differences Time-Domain (FDTD) algorithms are well established tools of computational electromagnetism. Because of their practical implementation as computer codes, they are affected by many numerical artefact and noise. In order to obtain better results we propose using Principal Component Analysis (PCA) based on multivariate statistical techniques. The PCA has been successfully used for the analysis of noise and spatial temporal structure in a sequence of images. It allows a straightforward discrimination between the numerical noise and the actual electromagnetic variables, and the quantitative estimation of their respective contributions. Besides, The GDTD results can be filtered to clean the effect of the noise. In this contribution we will show how the method can be applied to several FDTD simulations: the propagation of a pulse in vacuum, the analysis of two-dimensional photonic crystals. In this last case, PCA has revealed hidden electromagnetic structures related to actual modes of the photonic crystal.engjournal articlehttp://egmrs.powweb.com/EJS/PDF/vo291/19.pdfhttp://egmrs.powweb.com/EJS/PDF/vo291/index.htmhttp://cisne.sim.ucm.es/record=b3528557~S6*spiopen access537.533.3537.8535Finite-Differences Time-Domain(FDTD)computational electromagnetismPrincipal Component Analysis (PCA)photonic crystalElectromagnetismoÓptica (Física)Óptica física, óptica cuántica2202 Electromagnetismo2209.19 Óptica Física2209.19 Óptica física