We formulate the mask modeling as a parametric model order reduction problem. We then apply a robust reduction
technique to generate the compact mask model. Since this model is based on first principle, it naturally includes diffraction,
polarization and couplings, important effects that are poorly handled by the modified thin-mask model (MTMM). The
model generation involves only a few sampling solves of the governing equation, much fewer than that needed to generate
MTMM. Though the model evaluation takes marginally more CPU time than MTMM, the accuracy and the robustness of
the new model are based on much more rigorous theoretical foundation.
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