15 March 2016 Pixel-based mask optimization via particle swarm optimization algorithm for inverse lithography
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Abstract
An efficient pixel-based mask optimization method via particle swarm optimization (PSO) algorithm for inverse lithography is proposed. Because of the simplicity of principles, the ease of implementation and the efficiency of convergence, PSO has been widely used in many fields. In this study, PSO is used to solve the inverse problem of mask optimization. The pixel-based mask patterns are transformed into frequency space using discrete cosine transformation and the frequency components are encoded into particles. The pattern fidelity is adopted as the fitness function to evaluate these particles. The mask optimization method is implemented by updating the velocities and positions of these particles. Simulation results show that the image fidelity has been efficiently improved after using the proposed method.
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Lei Wang, Lei Wang, Sikun Li, Sikun Li, Xiangzhao Wang, Xiangzhao Wang, Chaoxing Yang, Chaoxing Yang, Feng Tang, Feng Tang, } "Pixel-based mask optimization via particle swarm optimization algorithm for inverse lithography", Proc. SPIE 9780, Optical Microlithography XXIX, 97801V (15 March 2016); doi: 10.1117/12.2230404; https://doi.org/10.1117/12.2230404
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