In our previous works, a convolutional neural network was developed which predicted diffraction amplitudes from extreme ultraviolet masks very fast. In this work, we reduce both the time for preparing the training data and the time for image intensity integration. We reduce the time for preparing the training data by applying weakly guiding approximation to 3D waveguide model. The model solves Helmholtz type coupled vector wave equations of two polarizations. The approximation decomposes the coupled vector wave equations into two scalar wave equations, reducing the computation time to solve the equations. Regarding the image intensity integration, Abbe’s theory has been used in electromagnetic simulations. Transmission cross coefficient (TCC) formula is known to be faster than Abbe’s theory, but TCC formula cannot be applied to source position dependent diffraction amplitudes in electromagnetic simulations. We derive source position dependent TCC formula starting from Abbe’s theory to accelerate the image intensity integration.
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