An efficient mask optimization method based on homotopy continuation technique

In sub-wavelength lithography, traditional resolution enhancement techniques (e.g., OPC) cannot guarantee the optimality of the mask. In this paper, we present a novel inverse lithography method to solve the mask optimization problem. Recognizing that when formulated on a pixel-by-pixel basis with partially coherent optical models, the problem is a large-scale nonlinear optimization problem, we cast the optimization flow into a homotopy framework and apply an efficient numerical continuation technique. Compared to earlier pixel-based inverse lithography methods, our homotopy approach is not only more efficient, but also capable of naturally addressing the mask manufactureability problem. Experiment results in a state-of-the-art lithography environment show that our method generates high fidelity wafer images, and is 100× faster than previously reported inverse lithography method.