The continuing reduction in feature dimensions and tightening of process constraints have led to an increasing demand for model-based approaches, which can efficiently explore the AF solution space, and achieve AF configurations not easily accessible via rules. In this work, we approach the AF placement problem as an inverse imaging problem. We discuss the generation of an inverse mask field and its use in determining the assist feature location. The results are compared with the single iteration intensity-field based AF placement with regard to symmetry, speed, memory, convergence, and accuracy. Several results with different pitches and illumination conditions are presented to demonstrate the robustness and adaptability of the inverse mask AF placement.
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