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Building accurate models for Mask Process Correction (MPC) is indispensable for manufacturing masks for advanced wafer production nodes. In recent years, contour-based model calibration is being increasingly studied as a supplement to standard gauge-based modeling. In this paper, we demonstrate a data processing flow for contour calibration of MPC models to overcome the issue of noisy input contours by averaging the measured contours of repeating patterns within the SEM image field-of-view (FOV). This method not only averages out the statistical noise in the incoming FOV contours, but also allows us to make the model calibration process more efficient.
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